{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.misc import derivative\n",
    "import logging\n",
    "from functools import lru_cache\n",
    "from scipy.optimize import least_squares\n",
    "import cvxpy as cp\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from scipy.interpolate import interp1d\n",
    "from scipy.integrate import solve_ivp\n",
    "from  functools import partial\n",
    "logger = logging.getLogger()\n",
    "logger.setLevel(logging.INFO)\n",
    "R0 = 6378*10**3#m   the radius of the Earth\n",
    "g0 = 9.81#m/s^2  Earth gravitational acceleration at R0\n",
    "m = 37362#kg   dimensional mass of the vehicle\n",
    "Sref = 149.4#m^2 the dimensional reference area of the vehicle\n",
    "omega = 7.2921*10**(-5)*np.sqrt(R0/g0)#rotational angular velocity of the earths\n",
    "kQ = 9.4369*10**(-5)\n",
    "Qmax = 800*10**3#W/m^2  maximum heat rate\n",
    "qmax = 14364#N/m^2   maximum dynamic pressure\n",
    "nmax = 2.5# in g0   maximum normal load factor\n",
    "vmin = 0/180*np.pi  # absolute minimum value of bank angle\n",
    "vmax = 165/180*np.pi  # absolute maximum value of bank angle\n",
    "H0 = 121.9*10**3#m   initial altitude\n",
    "Hf = 30.48*10**3#m   final altitude\n",
    "r0 = (H0+R0)/R0  #initial nondimensional radial distance from the center of the Earth\n",
    "rf = (Hf+R0)/R0  #final nondimensional radial distance from the center of the Earth\n",
    "theta0 = 237/180*np.pi  #initial longitude\n",
    "thetaf = 279/180*np.pi  #final longitude\n",
    "fai0 = -25/180*np.pi  #initial latitude\n",
    "faif = 28.61/180*np.pi  #final latitude\n",
    "V0 = 7626/np.sqrt(g0*R0)#  initial nondimensional velocity\n",
    "Vf = 908.15/np.sqrt(g0*R0)  #final nondimensional velocity\n",
    "gamma0 = -1.2493/180*np.pi #initial relative flight-path angle\n",
    "gammaf = np.array([-6,0])/180*np.pi#final relative flight-path angle\n",
    "polyfai0 = 45/180*np.pi  #initial heading angle of the relative velocity vector\n",
    "polyfaif = np.array([85,90])/180*np.pi  #final heading angle of the relative velocity vector\n",
    "delta = [20000/R0,20*np.pi/180,20*np.pi/180,20*np.pi/180,70*np.pi/180]  #trust-region constraint\n",
    "epsilon = [200/R0,0.05*np.pi/180,0.05*np.pi/180,0.05*np.pi/180,0.05*np.pi/180]  #stopping criteria\n",
    "kC = 1 # Variance Weights for Path Constraints\n",
    "kJ = 3 # Variance Weights for longitude and latitude\n",
    "N_points = 301\n",
    "n = 3  # Number of points in one dimension\n",
    "p = 2  # Degree of the polynomial\n",
    "d = 3  # Dimension of the random variable\n",
    "nOfS = n**d # Number of points in the stochastic space\n",
    "deterministic_idx = 14\n",
    "nOfP = int(np.math.factorial(p+d)/(np.math.factorial(p)*np.math.factorial(d))) # Number of terms in the polynomial\n",
    "# sigma_X0 = [1000/R0,0.1*np.pi/180,0.1*np.pi/180,0.1*np.pi/180,0.1*np.pi/180]\n",
    "deviation_Rho = 0.05 # standard deviation  of atmospheric density\n",
    "deviation_CL = 0.05  # standard deviation  of CL\n",
    "deviation_CD = 0.05  # standard deviation  of CD\n",
    "e0 = 1/r0-V0**2/2  #initial nondimensional energy\n",
    "ef = 1/rf-Vf**2/2  #final nondimensional energy\n",
    "e_values = None\n",
    "de = (ef-e0)/(N_points-1)\n",
    "dei = None\n",
    "dei_1 = None\n",
    "S_tmp,weights_tmp = np.polynomial.hermite.hermgauss(n)# Gauss-Hermite quadrature point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This Cell is a utility class used to assist in writing other functions.\n",
    "def find_kth_combination(k, m,n=n):\n",
    "    base = n ** (m - 1)\n",
    "    result = []\n",
    "\n",
    "    for i in range(m, 0, -1):\n",
    "        index = (k - 1) // base\n",
    "        result.append(index + 1)\n",
    "        k -= index * base\n",
    "        base //= n\n",
    "\n",
    "    return result\n",
    "def find_matrices_recursive(N,R, C, matrix, row, col, solutions):\n",
    "    if row == N:\n",
    "        if all([R[i] == 0 for i in range(N)]) and all([C[i] == 0 for i in range(N)]):\n",
    "            solutions.append([matrix[i].copy() for i in range(N)])\n",
    "        return\n",
    "    if R[row] == 0:\n",
    "        find_matrices_recursive(N,R, C, matrix, row + 1, 0, solutions)\n",
    "        return\n",
    "    if C[col] == 0:\n",
    "        if col + 1 < N:\n",
    "            find_matrices_recursive(N,R, C, matrix, row, col + 1, solutions)\n",
    "        else:\n",
    "            find_matrices_recursive(N,R, C, matrix, row + 1, 0, solutions)\n",
    "        return\n",
    "    next_row, next_col = (row, col + 1) if col + 1 < N else (row + 1, 0)\n",
    "    for value in range(min((R[row], C[col])) + 1):\n",
    "        ori = matrix[row][col]\n",
    "        matrix[row][col] = value\n",
    "        R[row] -= value  \n",
    "        C[col] -= value  \n",
    "        if R[row] >= 0 and C[col] >= 0:  \n",
    "            find_matrices_recursive(N,R, C, matrix, next_row, next_col, solutions) \n",
    "        R[row] += value  \n",
    "        C[col] += value  \n",
    "        matrix[row][col] = ori  \n",
    "@lru_cache(maxsize=None)\n",
    "def find_matrices(R, C):\n",
    "    assert len(R) == len(C), \"The length of R and C should be the same\"\n",
    "    N = len(R)\n",
    "    if isinstance(R, tuple):\n",
    "        R = list(R)  \n",
    "    if isinstance(C, tuple):\n",
    "        C = list(C)  \n",
    "    solutions = []\n",
    "    matrix = [[0 for _ in range(N)] for _ in range(N)]  \n",
    "    try:\n",
    "        find_matrices_recursive(N,R, C, matrix, 0, 0, solutions)\n",
    "    except Exception as e:\n",
    "        logging.debug(f\"find_matrices:R={R},C={C},e={e}\")\n",
    "        raise e\n",
    "    return solutions\n",
    "\n",
    "@lru_cache(maxsize=None)\n",
    "def comb(n, k):\n",
    "    return np.math.factorial(n) // (np.math.factorial(k) * np.math.factorial(n - k))\n",
    "def find_sequence_general(k, m):\n",
    "    '''按照m个数字的总和从小到大排列，找到第k个序列，如find_sequence_general(0,3)=[0,0,0],find_sequence_general(1,3)=[0,0,1]'''\n",
    "    n = 0\n",
    "    while True:\n",
    "        \n",
    "        count = comb(n + m - 1, m - 1)\n",
    "        if k < count:\n",
    "            break\n",
    "        k -= count\n",
    "        n += 1\n",
    "    \n",
    "    sequence = []\n",
    "    for _ in range(m - 1):\n",
    "        for x in range(n + 1):\n",
    "            if comb(n - x + m - 2, m - 2) > k:\n",
    "                sequence.append(x)\n",
    "                n -= x\n",
    "                m -= 1\n",
    "                break\n",
    "            else:\n",
    "                k -= comb(n - x + m - 2, m - 2)\n",
    "    sequence.append(n)\n",
    "    \n",
    "    return tuple(sequence)\n",
    "def evenly_sample_array(arr, num_samples=200):\n",
    "    n = len(arr)\n",
    "    indices = np.round(np.linspace(0, n - 1, num=num_samples)).astype(int)\n",
    "    sampled_points = arr[indices]\n",
    "    \n",
    "    return sampled_points\n",
    "def lsolution(func,upperbound):\n",
    "    r_solutions = []\n",
    "    for e in e_values:\n",
    "        if len(r_solutions)==0:\n",
    "            res = least_squares(lambda r:func(e,r)-upperbound,x0=r0, bounds =(1,np.inf),ftol=3e-16,xtol=3e-16,gtol=3e-16)\n",
    "        else:\n",
    "            res = least_squares(lambda r:func(e,r)-upperbound,x0=r_solutions[-1], bounds =(1,np.inf),ftol=3e-16,xtol=3e-16,gtol=3e-16)\n",
    "        if not res.success:\n",
    "            logging.debug(f\"lsolution:res={res}\")\n",
    "        assert len(res.x)==1,\"lsolution:res.x should be a scalar\"\n",
    "        r_solutions.append(res.x[0])\n",
    "    r_solutions = np.array(r_solutions)\n",
    "    return r_solutions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This Cell is a utility class used for Polynomial Chaos Expansions\n",
    "def Sj(j,sigma=(deviation_Rho,deviation_CL,deviation_CD)):\n",
    "    l = len(sigma)\n",
    "    ind = find_kth_combination(j,l)\n",
    "    return [np.sqrt(2)*sigma[i]*S_tmp[ind[i]-1] for i in range(l)]\n",
    "assert np.all(np.array(Sj(deterministic_idx))==0),\"Sj(deterministic_idx) should be all zeros\"\n",
    "def weightj(j,sigma=(deviation_Rho,deviation_CL,deviation_CD)):\n",
    "    l = len(sigma)\n",
    "    ind = find_kth_combination(j,l)\n",
    "    return np.prod([weights_tmp[ind[i]-1]/(np.sqrt(np.pi)) for i in range(l)])\n",
    "def hermite_polynomial(x,n,sigma=(deviation_Rho,deviation_CL,deviation_CD)):#计算Hermite多项式的值\n",
    "    if isinstance(x,(int,float)):\n",
    "        x = (x,)\n",
    "    if isinstance(sigma,(int,float)):\n",
    "        sigma = (sigma,)\n",
    "    variable_len = len(x)\n",
    "    assert variable_len == len(sigma), \"The length of x and sigma should be the same\"\n",
    "    seq = find_sequence_general(n,variable_len)\n",
    "    result = 1\n",
    "    for i in range(variable_len):\n",
    "        c = np.zeros(seq[i]+1)\n",
    "        c[seq[i]] = 1\n",
    "        result *= np.polynomial.hermite.hermval(x[i]/(np.sqrt(2)*sigma[i]),c)/((np.sqrt(2)*sigma[i])**seq[i])\n",
    "    norm = 1\n",
    "    for i,k in enumerate(seq):\n",
    "        norm *= np.math.factorial(k)\n",
    "    norm = norm**2\n",
    "    solutions = find_matrices(seq,seq)\n",
    "    tmp = 0\n",
    "    def sigma_inverse(sigma,m,n):\n",
    "        if m==n:\n",
    "            return 1/(sigma[m]**2)\n",
    "        else:\n",
    "            return 0\n",
    "    for solution in solutions:\n",
    "        tmp+=np.prod([(sigma_inverse(sigma,m,n))**solution[m][n]/np.math.factorial(solution[m][n]) for m in range(variable_len) for n in range(variable_len)])\n",
    "    norm = norm*tmp\n",
    "    return result/np.sqrt(norm)\n",
    "def coefficients_matrix(l,sigma=(deviation_Rho,deviation_CL,deviation_CD)):#计算多项式的系数,func(x,y,z)=\\sum_{i,j,k}c_{i,j,k}H_i(x/(sqrt(2)\\sigma))H_j(y/(sqrt(2)\\sigma))H_k(z/(sqrt(2)\\sigma))\n",
    "    '''求c_{i,j,k}的值，func是关于x,y,z的函数'''\n",
    "    return np.array([weightj(i,sigma)*hermite_polynomial(tuple(Sj(i,sigma)),l,sigma) for i in range(nOfS)])\n",
    "def quadratrue(f_vals):\n",
    "    integral = 0.5 * cp.sum(cp.multiply((f_vals[:-1] + f_vals[1:]) , (e_values.flatten()[1:] - e_values.flatten()[:-1])))\n",
    "    return integral\n",
    "def Variance_matrix(p=p,sigma=(deviation_Rho,deviation_CL,deviation_CD),isindex=False):#计算方差\n",
    "    '''计算标准差，func(x,y,z)是关于x,y,z的函数,p是多项式的阶数'''\n",
    "    result = 0\n",
    "    P = int(np.math.factorial(p+d)/(np.math.factorial(p)*np.math.factorial(d)))\n",
    "    for l in range(1,P+1):\n",
    "        tmp = coefficients_matrix(l,sigma)\n",
    "        result+=tmp.reshape(-1,1)@tmp.reshape(1,-1)\n",
    "    return result\n",
    "def Expectation_matrix(sigma=(deviation_Rho,deviation_CL,deviation_CD)):#计算期望\n",
    "    '''计算期望，func(x,y,z)是关于x,y,z的函数'''\n",
    "    return coefficients_matrix(0,sigma)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This Cell is a utility class used for Trajectory Dynamics parameters\n",
    "def Calcu_CLCD(alpha, mach,isCD=False):\n",
    "    x = alpha\n",
    "    y = mach\n",
    "    \n",
    "    mask = y<=5\n",
    "    if isCD:\n",
    "        CD = np.zeros_like(x)\n",
    "        a_D = 0.1908219490086461\n",
    "        b_D = 0.7921786756723015\n",
    "        c_D = 81.77767906793568\n",
    "        d_D = 0.7608546899234436\n",
    "        e_D = -0.06715377897523668\n",
    "        f_D = 4.809129538309562\n",
    "        g_D = -0.8220180925372075\n",
    "        z1_D = np.exp(-0.5 * (np.log(x / c_D) / d_D) ** 2)\n",
    "        z2_D = np.exp(-0.5 * ((y - f_D) / g_D) ** 2)\n",
    "        z_D = a_D + b_D * z1_D + e_D * z2_D\n",
    "        CD[mask] = z_D[mask]\n",
    "        a_D = 0.2893865934644147\n",
    "        b_D = 0.7101395427838309\n",
    "        c_D = 44.69254972733151\n",
    "        d_D = 12.43577575552023\n",
    "        e_D = -0.243653871914911\n",
    "        f_D = 5.428869369818743\n",
    "        g_D = 0.2330424954375339\n",
    "        hh_D = 1.098649201604347\n",
    "        z1_D = 1.0 / (1.0 + np.exp(-(x - c_D) / d_D))\n",
    "        z2_D = 1.0 / (1.0 + np.exp(-(y - f_D) / g_D))\n",
    "        z_D = a_D + b_D * z1_D + e_D * z2_D + hh_D * z1_D * z2_D\n",
    "        CD[~mask] = z_D[~mask]\n",
    "        return CD\n",
    "    else:\n",
    "        CL = np.zeros_like(x)\n",
    "        a_L = 0.6736442631404929\n",
    "        b_L = -0.2396729544298644\n",
    "        c_L = 0.02354634960855771\n",
    "        d_L = 0.5137518146743224\n",
    "        e_L = 35.7738334917245\n",
    "        f_L = 0.5482342780270542\n",
    "        z1_L = np.exp(-0.5 * (np.log(x / e_L) / f_L) ** 2)\n",
    "        z2_L = y * (b_L + c_L * y)\n",
    "        z_L = a_L + z2_L + d_L * z1_L\n",
    "        CL[mask] = z_L[mask]\n",
    "        a_L = -0.2361725195924329\n",
    "        b_L = 1.037601261644054\n",
    "        c_L = 50.11901193898274\n",
    "        d_L = 26.17064737989058\n",
    "        e_L = 0.8761093802115429\n",
    "        f_L = 4.857160518263465\n",
    "        g_L = -0.485173805363233\n",
    "        hh_L = -1.164121063690802\n",
    "        z1_L = np.exp(-0.5 * ((x - c_L) / d_L) ** 2)\n",
    "        z2_L = np.exp(-0.5 * ((y - f_L) / g_L) ** 2)\n",
    "        z_L = a_L + b_L * z1_L + e_L * z2_L + hh_L * z1_L * z2_L\n",
    "        CL[~mask] = z_L[~mask]\n",
    "        return CL\n",
    "CL = lambda alpha,mach,CLdelta=0: Calcu_CLCD(alpha,mach, isCD=False)*(1+CLdelta)#升力系数,alpha是攻角，单位度\n",
    "CD = lambda alpha,mach,CDdelta=0: Calcu_CLCD(alpha,mach, isCD=True)*(1+CDdelta)#阻力系数,alpha是攻角，单位度\n",
    "def calculate_temperature(heights):\n",
    "    is_number = isinstance(heights, (int, float))\n",
    "    if is_number:  # Check if the value is int or float\n",
    "        heights =np.array([heights])         # Convert it to a numpy array and return\n",
    "    T_0 = 288.15  # 初始温度，单位: K\n",
    "    temperatures = np.full(heights.shape, T_0)\n",
    "    layers = np.array([\n",
    "        (0, -6.5),\n",
    "        (11, 0.0),\n",
    "        (20, 1.0),\n",
    "        (32, 2.8),\n",
    "        (47, 0.0),\n",
    "        (51, -2.8),\n",
    "        (71, -2.0),\n",
    "        (85, np.nan)  # 85km以上的温度梯度不明确\n",
    "    ])\n",
    "    for i in range(len(layers) - 1):\n",
    "        # 高度属于当前层的掩码\n",
    "        mask = (heights >= layers[i, 0]) & (heights < layers[i+1, 0])\n",
    "        mask2 = (heights >= layers[i, 0])&(heights >= layers[i+1, 0])\n",
    "        # 计算对应层的温度变化并累加\n",
    "        temperatures += np.where(mask, layers[i, 1] * (heights - layers[i, 0]), 0)\n",
    "        temperatures += np.where(mask2, layers[i, 1] * (layers[i+1, 0] - layers[i, 0]), 0)\n",
    "    # 对于高度在最后一个已知层以上的情况，温度不变，仍然使用最后一个已知层的温度\n",
    "    if is_number:\n",
    "        return temperatures[0]\n",
    "    return temperatures\n",
    "def sound_speed(r):#声速，无量纲,r是无量纲\n",
    "    T = calculate_temperature((r-1)*R0/1000)\n",
    "    return (331.6+0.6*(T-273.15))/np.sqrt(g0*R0)\n",
    "def Rho(r,Rhodelta=0):#Atmospheric density in units of kg/m^3, where r is dimensionless, applicable for altitudes h>25km\n",
    "    return (1.225*np.exp(-(r-1)*R0*13.785e-5))*(1+Rhodelta)\n",
    "def Rho_r(r,Rhodelta=0):#derivative of Atmospheric density with respect to r\n",
    "    return -Rho(r,Rhodelta=Rhodelta)*R0*13.785e-5\n",
    "def alpha(Mach):#攻角，单位度\n",
    "    return 45-0.612*(np.maximum(10-Mach,0))**2\n",
    "def V(e,r):#速度，无量纲，e是能量，r是无量纲\n",
    "    assert np.all(e<=1/r),f\"V:e should be smaller than 1/r, e={e},r={r},e-1/r={e-1/r},np.max(e-1/r)={np.max(e-1/r)},np.argmax(e-1/r)={np.argmax(e-1/r)}\"\n",
    "    return np.sqrt(2*(1/r-e))\n",
    "def L(e,r,CLdelta=0,Rhodelta=0):#aerodynamic lift acceleration in g0\n",
    "    Mach = V(e,r)/sound_speed(r)\n",
    "    return 0.5*R0*Rho(r,Rhodelta=Rhodelta)*V(e,r)**2*Sref*CL(alpha(Mach),Mach,CLdelta=CLdelta)/(m)\n",
    "def D(e,r,CDdelta=0,Rhodelta=0):#aerodynamic drag acceleration in g0\n",
    "    Mach = V(e,r)/sound_speed(r)\n",
    "    return 0.5*R0*Rho(r,Rhodelta=Rhodelta)*V(e,r)**2*Sref*CD(alpha(Mach),Mach,CDdelta=CDdelta)/(m)\n",
    "def Dr(e,r,CDdelta=0,Rhodelta=0):#derivative of D with respect to r\n",
    "    Mach = V(e,r)/sound_speed(r)\n",
    "    dMach = -V(e,r)/(sound_speed(r)**2)*derivative(lambda r:sound_speed(r),r,dx=1e-7)\n",
    "    dCD = derivative(lambda mach:CD(alpha(mach),mach,CDdelta=CDdelta),Mach,dx=1e-7)\n",
    "    return 0.5*R0*Rho_r(r,Rhodelta=Rhodelta)*V(e,r)**2*Sref*CD(alpha(Mach),Mach,CDdelta=CDdelta)/(m)+\\\n",
    "            0.5*R0*Rho(r,Rhodelta=Rhodelta)*V(e,r)**2*Sref*dCD*dMach/(m)\n",
    "def n_value(e,r,CLdelta=0,CDdelta=0,Rhodelta=0):#normal load factor\n",
    "    return np.sqrt(L(e,r,CLdelta=CLdelta,Rhodelta=Rhodelta)**2+D(e,r,CDdelta=CDdelta,Rhodelta=Rhodelta)**2)\n",
    "def q_value(e,r,Rhodelta=0):#dynamic pressure\n",
    "    return 0.5*g0*R0*Rho(r,Rhodelta=Rhodelta)*V(e,r)**2\n",
    "def Q_value(e,r,Rhodelta=0):#heat rate\n",
    "    return kQ*np.sqrt(g0*R0)**3.15*np.sqrt(Rho(r,Rhodelta=Rhodelta))*(V(e,r))**3.15\n",
    "def sigma_t(t):#initial bank angle\n",
    "    if t < 160:\n",
    "        sigma = 0 \n",
    "    elif 160 <= t and t < 600:\n",
    "        sigma = -65 \n",
    "    elif 600 <= t and t < 1000:\n",
    "        sigma = -50 \n",
    "    else:\n",
    "        sigma = 45\n",
    "    return sigma"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This Cell is a utility class used for Convex Optimizaiton\n",
    "def Ak(r,theta,fai,gamma,polyfai):\n",
    "    '''计算A矩阵,r,theta,fai,gamma,polyfai是无量纲,且r[i,j]表示r(e_i,s_j),u=[cos(mu),sin(mu)]'''\n",
    "    S = np.array([Sj(i,sigma=(deviation_Rho,deviation_CL,deviation_CD)) for i in range(nOfS)])\n",
    "    Drk = Dr(e_values,r,CDdelta=S[:,2],Rhodelta=S[:,0])\n",
    "    Dk = D(e_values,r,CDdelta=S[:,2],Rhodelta=S[:,0])\n",
    "    sin_gammak = np.sin(gamma)\n",
    "    cos_gammak = np.cos(gamma)\n",
    "    sin_fai = np.sin(fai)\n",
    "    cos_fai = np.cos(fai)\n",
    "    tan_fai = np.tan(fai)\n",
    "    sin_polyfai = np.sin(polyfai)\n",
    "    cos_polyfai = np.cos(polyfai)\n",
    "    Vk = V(e_values,r)\n",
    "    a11 = -Drk*sin_gammak/(Dk**2)\n",
    "    a14 = cos_gammak/(Dk)\n",
    "    a21 = -(Drk/(r*Dk**2)+1/(r**2*Dk))*cos_gammak*sin_polyfai/cos_fai\n",
    "    a23 = cos_gammak*sin_polyfai*sin_fai/(r*Dk*cos_fai**2)\n",
    "    a24 = -sin_gammak*sin_polyfai/(r*Dk*cos_fai)\n",
    "    a25 = cos_gammak*cos_polyfai/(r*Dk*cos_fai)\n",
    "    a31 = -(Drk/(r*Dk**2)+1/(r**2*Dk))*cos_gammak*cos_polyfai\n",
    "    a34 = -sin_gammak*cos_polyfai/(r*Dk)\n",
    "    a35 = -cos_gammak*sin_polyfai/(r*Dk)\n",
    "    a41 = Drk*cos_gammak/(Dk**2*r)*(1/(r*Vk**2)-1)+cos_gammak/(Dk*r**2)*(2/(r*Vk**2)-1)\n",
    "    a44 = sin_gammak/(Dk*r)*(1/(r*Vk**2)-1)\n",
    "    a51 = -cos_gammak*sin_polyfai*tan_fai*(Drk/(r*Dk**2)+1/(r**2*Dk))\n",
    "    a53 = cos_gammak*sin_polyfai/(r*Dk*cos_fai**2)\n",
    "    a54 = -sin_gammak*sin_polyfai*tan_fai/(r*Dk)\n",
    "    a55 = cos_gammak*cos_polyfai*tan_fai/(r*Dk)\n",
    "    zeros = np.zeros_like(a11)\n",
    "    A =          [[a11,zeros,zeros,a14,zeros],\n",
    "                [a21,zeros,a23,a24,a25],\n",
    "                [a31,zeros,zeros,a34,a35],\n",
    "                [a41,zeros,zeros,a44,zeros],\n",
    "                [a51,zeros,a53,a54,a55]]\n",
    "    return np.array(A)\n",
    "def Bk(r,theta,fai,gamma,polyfai):\n",
    "    S = np.array([Sj(i,sigma=(deviation_Rho,deviation_CL,deviation_CD)) for i in range(nOfS)])\n",
    "    Drk = Dr(e_values,r,CDdelta=S[:,2],Rhodelta=S[:,0])\n",
    "    Dk = D(e_values,r,CDdelta=S[:,2],Rhodelta=S[:,0])\n",
    "    sin_gammak = np.sin(gamma)\n",
    "    cos_gammak = np.cos(gamma)\n",
    "    sin_fai = np.sin(fai)\n",
    "    cos_fai = np.cos(fai)\n",
    "    tan_fai = np.tan(fai)\n",
    "    sin_polyfai = np.sin(polyfai)\n",
    "    cos_polyfai = np.cos(polyfai)\n",
    "    Vk = V(e_values,r)\n",
    "    Lk = L(e_values,r,CLdelta=S[:,1],Rhodelta=S[:,0])\n",
    "    b41 = Lk/Dk/(Vk**2)\n",
    "    b52 = Lk/(Vk**2*cos_gammak*Dk)\n",
    "    zeros = np.zeros_like(b41)\n",
    "    B = [[zeros,zeros],\n",
    "            [zeros,zeros],\n",
    "            [zeros,zeros],\n",
    "            [b41,zeros],\n",
    "            [zeros,b52]]\n",
    "    return np.array(B)\n",
    "def f0(r,theta,fai,gamma,polyfai,is_test=False):\n",
    "    S = np.array([Sj(i,sigma=(deviation_Rho,deviation_CL,deviation_CD)) for i in range(nOfS)])\n",
    "    Drk = Dr(e_values,r,CDdelta=S[:,2],Rhodelta=S[:,0])\n",
    "    Dk = D(e_values,r,CDdelta=S[:,2],Rhodelta=S[:,0])\n",
    "    sin_gammak = np.sin(gamma)\n",
    "    cos_gammak = np.cos(gamma)\n",
    "    sin_fai = np.sin(fai)\n",
    "    cos_fai = np.cos(fai)\n",
    "    tan_fai = np.tan(fai)\n",
    "    sin_polyfai = np.sin(polyfai)\n",
    "    cos_polyfai = np.cos(polyfai)\n",
    "    Vk = V(e_values,r)\n",
    "    Lk = L(e_values,r,CLdelta=S[:,1],Rhodelta=S[:,0])\n",
    "    f1 = 1/Dk*sin_gammak\n",
    "    f2 = cos_gammak*sin_polyfai/(r*Dk*cos_fai)\n",
    "    f3 = cos_gammak*cos_polyfai/(r*Dk)\n",
    "    f4 = (1/Dk-1/(r*Vk**2*Dk))*cos_gammak/r\n",
    "    f5 = cos_gammak*sin_polyfai*tan_fai/(r*Dk)\n",
    "    f02 = np.array([f1,f2,f3,f4,f5])\n",
    "    return np.array(f02)\n",
    "def f_omega_k(r,theta,fai,gamma,polyfai,is_test=False):\n",
    "    S = np.array([Sj(i,sigma=(deviation_Rho,deviation_CL,deviation_CD)) for i in range(nOfS)])\n",
    "    Drk = Dr(e_values,r,CDdelta=S[:,2],Rhodelta=S[:,0])\n",
    "    Dk = D(e_values,r,CDdelta=S[:,2],Rhodelta=S[:,0])\n",
    "    sin_gammak = np.sin(gamma)\n",
    "    cos_gammak = np.cos(gamma)\n",
    "    sin_fai = np.sin(fai)\n",
    "    cos_fai = np.cos(fai)\n",
    "    tan_fai = np.tan(fai)\n",
    "    tan_gammak = np.tan(gamma)\n",
    "    sin_polyfai = np.sin(polyfai)\n",
    "    cos_polyfai = np.cos(polyfai)\n",
    "    Vk = V(e_values,r)\n",
    "    Lk = L(e_values,r,CLdelta=S[:,1],Rhodelta=S[:,0])\n",
    "    b4 = (2*omega*Vk*cos_fai*sin_polyfai+omega**2*r*cos_fai*(cos_gammak*cos_fai+sin_gammak*cos_polyfai*sin_fai))/(Vk**2*Dk)\n",
    "    b5 = (-2*omega*Vk*(tan_gammak*cos_polyfai*cos_fai-sin_fai)+omega**2*r*sin_polyfai*sin_fai*cos_fai/cos_gammak)/(Vk**2*Dk)\n",
    "    f_omega = np.array([np.zeros_like(b4),np.zeros_like(b4),np.zeros_like(b4),b4,b5])\n",
    "    return np.array(f_omega)\n",
    "def bk(r,theta,fai,gamma,polyfai,is_test=False):\n",
    "    f0k = f0(r,theta,fai,gamma,polyfai)\n",
    "    f_omega_kk = f_omega_k(r,theta,fai,gamma,polyfai)\n",
    "    Akk = Ak(r,theta,fai,gamma,polyfai)\n",
    "    xk  = [r,theta,fai,gamma,polyfai]\n",
    "    result = [f0k[i] for i in range(5)]\n",
    "    for i in range(5):\n",
    "        tmp = 0\n",
    "        for j in range(5):\n",
    "            tmp = tmp+(Akk[i,j]*xk[j])\n",
    "        result[i] = result[i]-tmp+f_omega_kk[i]\n",
    "    return np.array(result)\n",
    "def dXdt(r,theta,fai,gamma,polyfai,e,cos_sigma,sin_sigma,j=deterministic_idx,Rhodelta1=None,CLdelta1=None,CDdelta1=None):#V:m/s,r:m,theta,fai,gamma,polyfai:rad\n",
    "    if Rhodelta1 is None and CLdelta1 is None and CDdelta1 is None:\n",
    "        Rhodelta = lambda k: Sj(k)[0]\n",
    "        CLdelta = lambda k: Sj(k)[1]\n",
    "        CDdelta = lambda k: Sj(k)[2]\n",
    "    else:\n",
    "        Rhodelta = lambda k: Rhodelta1\n",
    "        CLdelta = lambda k: CLdelta1\n",
    "        CDdelta = lambda k: CDdelta1\n",
    "    Vk = V(e,r)\n",
    "    Dk = D(e,r,CDdelta=CDdelta(j),Rhodelta=Rhodelta(j))\n",
    "    Lk = L(e,r,CLdelta=CLdelta(j),Rhodelta=Rhodelta(j))\n",
    "    cos_gamma = np.cos(gamma)\n",
    "    sin_gamma = np.sin(gamma)\n",
    "    cos_fai =  np.cos(fai)\n",
    "    sin_fai = np.sin(fai)\n",
    "    cos_polyfai =np.cos(polyfai)\n",
    "    sin_polyfai =  np.sin(polyfai)\n",
    "    tan_fai =  np.tan(fai)\n",
    "    tan_gamma =  np.tan(gamma)\n",
    "    dr = Vk*sin_gamma\n",
    "    dtheta = Vk*cos_gamma*sin_polyfai/(r*cos_fai)\n",
    "    dfai = Vk*cos_gamma*cos_polyfai/(r)\n",
    "    dV = -Dk-sin_gamma/r**2+omega**2*r*cos_fai*(sin_gamma*cos_fai-cos_gamma*sin_fai*cos_polyfai)\n",
    "    dgamma = 1/Vk*(Lk*cos_sigma+(Vk**2-1/r)*cos_gamma/r+2*omega*Vk*cos_fai*sin_polyfai+omega**2*r*cos_fai*(cos_gamma*cos_fai+sin_gamma*sin_fai*cos_polyfai))\n",
    "    dpolyfai = 1/Vk*(Lk*sin_sigma/(cos_gamma)+Vk**2/r*cos_gamma*sin_polyfai*tan_fai+2*omega*Vk*(sin_fai-tan_gamma*cos_polyfai*cos_fai)+omega**2*r/cos_gamma*sin_polyfai*sin_fai*cos_fai)\n",
    "    return np.array([dr,dtheta,dfai,dgamma,dpolyfai,dV])\n",
    "def dedt(r,theta,fai,gamma,polyfai,e,j=deterministic_idx):#V:m/s,r:m,theta,fai,gamma,polyfai:rad\n",
    "    assert np.isclose(e,1/r-V(e,r)**2/2),f\"{e}!={1/r-V(e,r)**2/2},r={r},V={V(e,r)}\"\n",
    "    Rhodelta = lambda k: Sj(k)[0]\n",
    "    CLdelta = lambda k: Sj(k)[1]\n",
    "    CDdelta = lambda k: Sj(k)[2]\n",
    "    Dk  =D(e,r,CDdelta=CDdelta(j),Rhodelta=Rhodelta(j))\n",
    "    return Dk*V(e,r)\n",
    "def dXde(r,theta,fai,gamma,polyfai,Vk,cos_sigma,sin_sigma,j=deterministic_idx):#V:m/s,r:m,theta,fai,gamma,polyfai:rad\n",
    "    e = 1/r-Vk**2/2\n",
    "    assert np.isclose(V(e,r),Vk),f\"{V(e,r)}!={Vk},e={e},r={r}\"\n",
    "    dxdt = dXdt(r,theta,fai,gamma,polyfai,e,cos_sigma,sin_sigma,j)\n",
    "    dedt_val = dedt(r,theta,fai,gamma,polyfai,e,j)\n",
    "    return (dxdt/dedt_val)\n",
    "def sigma_e_function():\n",
    "    gammak=[float(gamma0)]\n",
    "    thetak = [float(theta0)]\n",
    "    faik = [float(fai0)]\n",
    "    polyfaik = [float(polyfai0)]\n",
    "    rk = [float(r0)]\n",
    "    Vk = [float(V0)]\n",
    "    ek = [float(e0)]\n",
    "    tk = [0]\n",
    "    dt = 1/np.sqrt(R0/g0)\n",
    "    while ek[-1]<=ef:\n",
    "        dXdt_val = dXdt(rk[-1],thetak[-1],faik[-1],gammak[-1],polyfaik[-1],ek[-1],np.cos(sigma_t(tk[-1]*np.sqrt(R0/g0))/180*np.pi),np.sin(sigma_t(tk[-1]*np.sqrt(R0/g0))/180*np.pi),deterministic_idx)\n",
    "        rk.append(float(rk[-1]+dt*dXdt_val[0]))\n",
    "        thetak.append(float(thetak[-1]+dt*dXdt_val[1]))\n",
    "        faik.append(float(faik[-1]+dt*dXdt_val[2]))\n",
    "        gammak.append(float(gammak[-1]+dt*dXdt_val[3]))\n",
    "        polyfaik.append(float(polyfaik[-1]+dt*dXdt_val[4]))\n",
    "        Vk.append(float(Vk[-1]+dt*dXdt_val[5]))\n",
    "        ek.append(float(1/rk[-1]-Vk[-1]**2/2))\n",
    "        tk.append(float(tk[-1]+dt))\n",
    "    rk = np.array(rk)\n",
    "    thetak = np.array(thetak)\n",
    "    faik = np.array(faik)\n",
    "    gammak = np.array(gammak)\n",
    "    polyfaik = np.array(polyfaik)\n",
    "    Vk = np.array(Vk)\n",
    "    sigma = np.array([sigma_t(t*np.sqrt(R0/g0)) for t in tk])\n",
    "    tk = np.array(tk)\n",
    "    ek = np.array(ek)\n",
    "    f = interp1d(ek.flatten(),sigma.flatten(), kind='linear',fill_value='extrapolate')\n",
    "    return f\n",
    "def init_e_values():\n",
    "    global e_values\n",
    "    global dei,dei_1\n",
    "    sigma_e = sigma_e_function()\n",
    "    results_original = solve_ivp(lambda e,y:dXde(y[0],y[1],y[2],y[3],y[4],y[5],np.cos(sigma_e(e)/180*np.pi),np.sin(sigma_e(e)/180*np.pi),deterministic_idx), [e0,ef], np.array([r0,theta0,fai0,gamma0,polyfai0,V0]),max_step=de/2,method = 'LSODA')\n",
    "    e_values = evenly_sample_array(results_original.t,N_points)\n",
    "    dei = np.insert(e_values[1:]-e_values[:-1],0,0)\n",
    "    dei_1 = np.insert(e_values[1:]-e_values[:-1],-1,0)\n",
    "    e_values = e_values.reshape(-1,1)\n",
    "    dei = dei.reshape(-1,1)\n",
    "    dei_1 = dei_1.reshape(-1,1)\n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This Cell is a utility class used for Convex Problem definition\n",
    "def objective(rk,thetak,faik,gammak,polyfaik,r,theta,fai,polyfai,relaxVariable,epsilon_polyfai1=1e-1,c1=[1,1,1],isdeterministic=False):\n",
    "    '''目标函数,rk,thetak,faik,gammak,polyfaik是无量纲,且r[i,j]表示r(e_i,s_j),uk=[cos(mu),sin(mu)]'''\n",
    "    c = np.array(c1)\n",
    "    S = np.array([Sj(i,sigma=(deviation_Rho,deviation_CL,deviation_CD)) for i in range(nOfS)])\n",
    "    epsilon_polyfai = epsilon_polyfai1\n",
    "    Dk_ = D(e_values,rk,CDdelta=S[:,2],Rhodelta=S[:,0])\n",
    "    Vk_ = V(e_values,rk)\n",
    "    Dr_k = Dr(e_values,rk,CDdelta=S[:,2],Rhodelta=S[:,0])\n",
    "    objk_r = -1/((Dk_*Vk_)**2)*(Dr_k*Vk_)\n",
    "    objk = 1/(Dk_*Vk_)\n",
    "    if isdeterministic:\n",
    "        return epsilon_polyfai*quadratrue(polyfai[:,deterministic_idx])+quadratrue(objk[:,deterministic_idx]+cp.multiply(objk_r[:,deterministic_idx],(r[:,deterministic_idx]-rk[:,deterministic_idx])))+sum([c[i]*relaxVariable[i] for i in range(len(relaxVariable))])\n",
    "    else:\n",
    "        expectation_matrix = Expectation_matrix()\n",
    "        coefficients_mat = Variance_matrix()\n",
    "        variance_obj = 0\n",
    "        variance_obj = cp.quad_form(theta[N_points-1,:].T,coefficients_mat)\n",
    "        variance_obj = variance_obj+cp.quad_form(fai[N_points-1,:].T,coefficients_mat)\n",
    "        obj = epsilon_polyfai*quadratrue(polyfai@expectation_matrix)+quadratrue((objk+cp.multiply(objk_r,(r-rk)))@expectation_matrix)+sum([c[i]*relaxVariable[i] for i in range(len(relaxVariable))])+kJ*variance_obj\n",
    "        return obj\n",
    "def init(u_val=None):#获取积分初值\n",
    "    if u_val is None:\n",
    "        sigma_e = sigma_e_function()\n",
    "    else:\n",
    "        sigma_e = interp1d(e_values.flatten(),np.arctan2(u_val[1],u_val[0]).flatten()/np.pi*180, kind='linear',fill_value='extrapolate')\n",
    "    results = [solve_ivp(lambda e,y:dXde(y[0],y[1],y[2],y[3],y[4],y[5],np.cos(sigma_e(e)/180*np.pi),np.sin(sigma_e(e)/180*np.pi),j), [e0,ef], np.array([r0,theta0,fai0,gamma0,polyfai0,V0]),max_step=de,method = 'RK45',rtol=1e-8,atol=1e-8,t_eval=e_values.flatten()) for j in range(nOfS)]\n",
    "    rk = np.ones((N_points,nOfS))*np.concatenate([results[j].y[0,:].reshape(-1,1) for j in range(nOfS)],axis=1)\n",
    "    thetak = np.ones((N_points,nOfS))*np.concatenate([results[j].y[1,:].reshape(-1,1) for j in range(nOfS)],axis=1)\n",
    "    faik = np.ones((N_points,nOfS))*np.concatenate([results[j].y[2,:].reshape(-1,1) for j in range(nOfS)],axis=1)\n",
    "    gammak = np.ones((N_points,nOfS))*np.concatenate([results[j].y[3,:].reshape(-1,1) for j in range(nOfS)],axis=1)\n",
    "    polyfaik = np.ones((N_points,nOfS))*np.concatenate([results[j].y[4,:].reshape(-1,1) for j in range(nOfS)],axis=1)\n",
    "    return rk,thetak,faik,gammak,polyfaik\n",
    "@lru_cache(maxsize=1)\n",
    "def path_constrain_init():\n",
    "    Rhodelta = lambda j: Sj(j,sigma=(deviation_Rho,deviation_CL,deviation_CD))[0]\n",
    "    CLdelta = lambda j: Sj(j,sigma=(deviation_Rho,deviation_CL,deviation_CD))[1]\n",
    "    CDdelta = lambda j: Sj(j,sigma=(deviation_Rho,deviation_CL,deviation_CD))[2]\n",
    "    lQ = [lsolution(partial(Q_value,Rhodelta=Rhodelta(j)),Qmax) for j in range(nOfS)]#lQ[j][i]表示lQ(e_i,s_j)\n",
    "    lq = [lsolution(partial(q_value,Rhodelta=Rhodelta(j)),qmax) for j in range(nOfS)]#lq[j][i]表示lq(e_i,s_j)\n",
    "    ln = [lsolution(partial(n_value,Rhodelta=Rhodelta(j),CDdelta=CDdelta(j),CLdelta=CLdelta(j)),nmax) for j in range(nOfS)]#ln[j][i]表示ln(e_i,s_j)\n",
    "    path_constrain = np.array([[max((lQ[j][i],lq[j][i],ln[j][i])) for j in range(nOfS)] for i in range(N_points)])\n",
    "    return path_constrain\n",
    "def kineticEquation_constrain(rk,thetak,faik,gammak,polyfaik,r,theta,fai,gamma,polyfai,u,isdeterministic=False):\n",
    "    Akk = Ak(rk,thetak,faik,gammak,polyfaik)\n",
    "    Bkk = Bk(rk,thetak,faik,gammak,polyfaik)\n",
    "    bkk = bk(rk,thetak,faik,gammak,polyfaik)\n",
    "    Akki = np.eye(5).reshape(5,5,1,1)-Akk*dei.reshape(1,1,-1,1)/2\n",
    "    Akki_1 = np.eye(5).reshape(5,5,1,1)+Akk*dei_1.reshape(1,1,-1,1)/2\n",
    "    Bkki,Bkki_1= Bkk*dei.reshape(1,1,-1,1)/2, Bkk*dei_1.reshape(1,1,-1,1)/2\n",
    "    bkki,bkki_1 = bkk*dei.reshape(1,-1,1)/2,bkk*dei_1.reshape(1,-1,1)/2\n",
    "    X = [r,theta,fai,gamma,polyfai]\n",
    "    result_i_1 = []\n",
    "    result_i = []\n",
    "    for i in range(5):\n",
    "        tmpi = np.zeros((N_points,nOfS))#Xi\n",
    "        tmpi_1 = np.zeros((N_points,nOfS))#Xi_1\n",
    "        for j in range(5):\n",
    "            tmpi = tmpi+cp.multiply(Akki[i,j],X[j])\n",
    "            tmpi_1 = tmpi_1+cp.multiply(Akki_1[i,j],X[j])\n",
    "        for j in range(2):\n",
    "            tmpi = tmpi+cp.multiply(-Bkki[i,j],u[j])\n",
    "            tmpi_1 = tmpi_1+cp.multiply(Bkki_1[i,j],u[j])\n",
    "        tmpi = tmpi-bkki[i]\n",
    "        tmpi_1 = tmpi_1+bkki_1[i]\n",
    "        result_i_1.append(tmpi_1)\n",
    "        result_i.append(tmpi)\n",
    "    assert len(result_i_1) == len(result_i),f\"len(result_i_1)={len(result_i_1)},len(result_i)={len(result_i)}\"\n",
    "    if isdeterministic:\n",
    "        return [result_i[k][1:,deterministic_idx]==result_i_1[k][:-1,deterministic_idx] for k in range(len(result_i))]\n",
    "    else:\n",
    "        return [result_i[k][1:,:]==result_i_1[k][:-1,:] for k in range(len(result_i))]\n",
    "def InitialState_constraint(x,initialState,relaxVariable=None,isdeterministic=False,sigma_x=0):\n",
    "    if isdeterministic:\n",
    "        if relaxVariable is not None:\n",
    "            return [cp.abs(x[0,deterministic_idx]-initialState)<=relaxVariable]\n",
    "        else:\n",
    "            return [x[0,deterministic_idx]==initialState]\n",
    "    else:\n",
    "        expectation_mat = Expectation_matrix()\n",
    "        variance_matrix = Variance_matrix()\n",
    "        if relaxVariable is not None:\n",
    "            if sigma_x==0:\n",
    "                return [cp.abs(x[0,:]-initialState)<=relaxVariable]\n",
    "            else:\n",
    "                return [cp.abs(x[0,:]@expectation_mat-initialState)<=relaxVariable,cp.quad_form(x[0,:].T,variance_matrix)<=sigma_x**2]\n",
    "        else:\n",
    "            if sigma_x==0:\n",
    "                return [x[0,:]==initialState]\n",
    "            else:\n",
    "                return [x[0,:]@expectation_mat==initialState,cp.quad_form(x[0,:].T,variance_matrix)<=sigma_x**2]\n",
    "def FinalState_constraint(x,finalState,relaxVariable=None,isdeterministic=False):#终态的方差不约束\n",
    "    if isdeterministic:\n",
    "        if relaxVariable is not None:\n",
    "            return [cp.abs(x[N_points-1,deterministic_idx]-finalState)<=relaxVariable]\n",
    "        else:\n",
    "            if len(np.array([finalState]).flatten())==2:\n",
    "                return [x[N_points-1,deterministic_idx]>=finalState[0],x[N_points-1,deterministic_idx]<=finalState[1]]\n",
    "            else:\n",
    "                return [x[N_points-1,deterministic_idx]==finalState]\n",
    "    else:\n",
    "        expectation_mat = Expectation_matrix()\n",
    "        if relaxVariable is not None:\n",
    "            return [cp.abs(x[N_points-1,:]@expectation_mat-finalState)<=relaxVariable]\n",
    "        else:\n",
    "            if len(np.array([finalState]).flatten())==2:\n",
    "                return [x[N_points-1,:]@expectation_mat>=finalState[0],x[N_points-1,:]@expectation_mat<=finalState[1]]\n",
    "            else:\n",
    "                return [x[N_points-1,:]@expectation_mat==finalState]\n",
    "def u_constrain(u):\n",
    "    return [u[0]>=np.cos(vmax),u[0]<=np.cos(vmin),u[0]**2+u[1]**2<=1]\n",
    "def trustDomain_constrain(x,xk,delta_x,isdeterministic=False):\n",
    "    if isdeterministic:\n",
    "        return [cp.abs(x[:,deterministic_idx]-xk[:,deterministic_idx])<=delta_x]\n",
    "    else:\n",
    "        return [cp.abs(x-xk)<=delta_x]\n",
    "def create_variable():\n",
    "    r = cp.Variable((N_points, nOfS),pos=True)\n",
    "    theta = cp.Variable((N_points, nOfS))\n",
    "    fai = cp.Variable((N_points, nOfS))\n",
    "    gamma = cp.Variable((N_points, nOfS))\n",
    "    polyfai = cp.Variable((N_points, nOfS))\n",
    "    u = [cp.Variable((N_points, 1)),cp.Variable((N_points, 1))]\n",
    "    return r,theta,fai,gamma,polyfai,u"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This Cell is a utility class used for Convex Problem solving\n",
    "def solve(obj,constrains):\n",
    "    prob = cp.Problem(cp.Minimize(obj), constrains)\n",
    "    logging.info(\"objective is done, Start solving\")\n",
    "    prob.solve(solver=cp.MOSEK,warm_start=True,verbose=False,ignore_dpp = True)\n",
    "    if prob.status != cp.OPTIMAL and prob.status != cp.OPTIMAL_INACCURATE:\n",
    "        return False\n",
    "    else:\n",
    "        logging.info(\"MOSEK Solver is done\")\n",
    "        return True\n",
    "def iteration(rk,thetak,faik,gammak,polyfaik,r,theta,fai,gamma,polyfai,u,isdeterministic=False):\n",
    "    relaxVariable = [cp.Variable(1),cp.Variable(1)]\n",
    "    Constrains  =[]\n",
    "    X0 = [r0,theta0,fai0,gamma0,polyfai0]\n",
    "    Xf = [rf,thetaf,faif,gammaf,polyfaif]\n",
    "    X  = [r,theta,fai,gamma,polyfai]\n",
    "    Xk = [rk,thetak,faik,gammak,polyfaik]\n",
    "    print(\"-\"*25,\"prepare Constrains\",\"-\"*25)\n",
    "    #初态约束\n",
    "    for i in range(5):\n",
    "        Constrains.extend(InitialState_constraint(X[i],X0[i],isdeterministic=isdeterministic))\n",
    "    #终态约束\n",
    "    for i in range(5):   \n",
    "        if i==1 or i==2:#经度和纬度需要松弛变量\n",
    "            Constrains.extend(FinalState_constraint(X[i],Xf[i],relaxVariable=relaxVariable[i-1],isdeterministic=isdeterministic))\n",
    "        else:\n",
    "            Constrains.extend(FinalState_constraint(X[i],Xf[i],isdeterministic=isdeterministic))\n",
    "    #路径约束\n",
    "    path_constrain = path_constrain_init()\n",
    "    if isdeterministic:\n",
    "        Constrains.append(r[:,deterministic_idx]>=path_constrain[:,deterministic_idx])\n",
    "    else:\n",
    "        expectation_mat = Expectation_matrix()\n",
    "        coefficients_mat = Variance_matrix()\n",
    "        rk_variance = np.diagonal(rk@coefficients_mat@rk.T).copy()\n",
    "        path_constrain_variance = np.diagonal(path_constrain@coefficients_mat@path_constrain.T).copy()\n",
    "        path_constrain_expectation = path_constrain@expectation_mat\n",
    "        r_expectation = r@expectation_mat\n",
    "        rk_variance[rk_variance<0]=0\n",
    "        path_constrain_variance[path_constrain_variance<0]=0\n",
    "        Constrains.append(r_expectation>=path_constrain_expectation+kC*(np.sqrt(rk_variance)+np.sqrt(path_constrain_variance)))\n",
    "    #动力学方程约束\n",
    "    Constrains.extend(kineticEquation_constrain(rk,thetak,faik,gammak,polyfaik,r,theta,fai,gamma,polyfai,u,isdeterministic=isdeterministic))\n",
    "    #控制约束\n",
    "    Constrains.extend(u_constrain(u))\n",
    "    #有效取值范围的约束\n",
    "    Constrains.append(r>=1)\n",
    "    for i in range(len(relaxVariable)):\n",
    "        Constrains.append(relaxVariable[i]>=0)\n",
    "    #信赖域约束\n",
    "    for i in range(5):\n",
    "        Constrains.extend(trustDomain_constrain(X[i],Xk[i],delta[i],isdeterministic=isdeterministic))\n",
    "    obj = objective(rk,thetak,faik,gammak,polyfaik,r,theta,fai,polyfai,relaxVariable,c1=[1]*len(relaxVariable),isdeterministic=isdeterministic,epsilon_polyfai1=0.5)\n",
    "    print(\"-\"*25,\"Constrains are done, Start solving\",\"-\"*25)\n",
    "    return solve(obj,Constrains)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initialization is done\n",
      "------------------------- prepare Constrains -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:objective is done, Start solving\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------- Constrains are done, Start solving -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:MOSEK Solver is done\n",
      "INFO:root:objective is done, Start solving\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0 done, max dXk: 5.108221117257313\n",
      "------------------------- prepare Constrains -------------------------\n",
      "------------------------- Constrains are done, Start solving -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:MOSEK Solver is done\n",
      "INFO:root:objective is done, Start solving\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 1 done, max dXk: 0.06771060130824358\n",
      "------------------------- prepare Constrains -------------------------\n",
      "------------------------- Constrains are done, Start solving -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:MOSEK Solver is done\n",
      "INFO:root:objective is done, Start solving\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 2 done, max dXk: 0.011982416613597058\n",
      "------------------------- prepare Constrains -------------------------\n",
      "------------------------- Constrains are done, Start solving -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:MOSEK Solver is done\n",
      "INFO:root:objective is done, Start solving\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 3 done, max dXk: 0.005679207021476673\n",
      "------------------------- prepare Constrains -------------------------\n",
      "------------------------- Constrains are done, Start solving -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:MOSEK Solver is done\n",
      "INFO:root:objective is done, Start solving\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 4 done, max dXk: 0.0010713882606230296\n",
      "------------------------- prepare Constrains -------------------------\n",
      "------------------------- Constrains are done, Start solving -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:MOSEK Solver is done\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 5 done, max dXk: 0.0003017597628345303\n",
      "Optimization1 is done,start optimization2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:objective is done, Start solving\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------- prepare Constrains -------------------------\n",
      "------------------------- Constrains are done, Start solving -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:MOSEK Solver is done\n",
      "INFO:root:objective is done, Start solving\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0 done, max dXk: 0.13106371933455652\n",
      "------------------------- prepare Constrains -------------------------\n",
      "------------------------- Constrains are done, Start solving -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:MOSEK Solver is done\n",
      "INFO:root:objective is done, Start solving\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 1 done, max dXk: 0.04555773065202204\n",
      "------------------------- prepare Constrains -------------------------\n",
      "------------------------- Constrains are done, Start solving -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:MOSEK Solver is done\n",
      "INFO:root:objective is done, Start solving\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 2 done, max dXk: 0.02830255023455755\n",
      "------------------------- prepare Constrains -------------------------\n",
      "------------------------- Constrains are done, Start solving -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:MOSEK Solver is done\n",
      "INFO:root:objective is done, Start solving\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 3 done, max dXk: 0.021682984438370412\n",
      "------------------------- prepare Constrains -------------------------\n",
      "------------------------- Constrains are done, Start solving -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:MOSEK Solver is done\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 4 done, max dXk: 0.011333719589264823\n",
      "------------------------- prepare Constrains -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:objective is done, Start solving\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------- Constrains are done, Start solving -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:MOSEK Solver is done\n",
      "INFO:root:objective is done, Start solving\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 5 done, max dXk: 0.004530956929271468\n",
      "------------------------- prepare Constrains -------------------------\n",
      "------------------------- Constrains are done, Start solving -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:MOSEK Solver is done\n",
      "INFO:root:objective is done, Start solving\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 6 done, max dXk: 0.001171057755384286\n",
      "------------------------- prepare Constrains -------------------------\n",
      "------------------------- Constrains are done, Start solving -------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:MOSEK Solver is done\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 7 done, max dXk: 0.0004071762934647616\n",
      "Optimization is done\n"
     ]
    }
   ],
   "source": [
    "# This Cell is main Program\n",
    "init_e_values()\n",
    "r,theta,fai,gamma,polyfai,u = create_variable()\n",
    "rk,thetak,faik,gammak,polyfaik = init()\n",
    "isok = False\n",
    "print(\"Initialization is done\")\n",
    "for i in range(100):\n",
    "    isok = iteration(rk,thetak,faik,gammak,polyfaik,r,theta,fai,gamma,polyfai,u,isdeterministic=True)\n",
    "    if not isok:\n",
    "        print('-'*100)\n",
    "        print(\"optimization1 failed\")\n",
    "        print('*'*100)\n",
    "        break\n",
    "    \n",
    "    rk1 = np.ones_like(rk)*r.value\n",
    "    thetak1 = np.ones_like(thetak)*theta.value\n",
    "    faik1 = np.ones_like(faik)*fai.value\n",
    "    gammak1 = np.ones_like(gammak)*gamma.value\n",
    "    polyfaik1 = np.ones_like(polyfaik)*polyfai.value\n",
    "    u_val = [u[0].value,u[1].value]\n",
    "    Xk = np.array([rk,thetak,faik,gammak,polyfaik])\n",
    "    Xk1 = np.array([rk1,thetak1,faik1,gammak1,polyfaik1])\n",
    "    dXk = np.max(np.abs(Xk1-Xk),axis=(-1,-2))\n",
    "    print(\"Iteration\",i,\"done,\",\"max dXk:\",np.max(dXk))\n",
    "    if np.all(np.greater(np.array(epsilon),dXk)):\n",
    "        break\n",
    "    rk = rk1.copy()\n",
    "    thetak = thetak1.copy()\n",
    "    faik = faik1.copy()\n",
    "    gammak = gammak1.copy()\n",
    "    polyfaik = polyfaik1.copy()\n",
    "if isok:\n",
    "    DO_Xk = [Xk1[i][:,deterministic_idx] for i in range(5)]\n",
    "    DO_u = u_val\n",
    "    print(\"Optimization1 is done,start optimization2\")\n",
    "    rk,thetak,faik,gammak,polyfaik = init(u_val)\n",
    "    for i in range(100):\n",
    "        isok = iteration(rk,thetak,faik,gammak,polyfaik,r,theta,fai,gamma,polyfai,u,isdeterministic=False)\n",
    "        if not isok:\n",
    "            print('-'*100)\n",
    "            print(\"optimization2 failed\")\n",
    "            print('*'*100)\n",
    "            break\n",
    "        rk1 = np.ones_like(rk)*r.value\n",
    "        thetak1 = np.ones_like(thetak)*theta.value\n",
    "        faik1 = np.ones_like(faik)*fai.value\n",
    "        gammak1 = np.ones_like(gammak)*gamma.value\n",
    "        polyfaik1 = np.ones_like(polyfaik)*polyfai.value\n",
    "        u_val = [u[0].value,u[1].value]\n",
    "        Xk = np.array([rk,thetak,faik,gammak,polyfaik])\n",
    "        Xk1 = np.array([rk1,thetak1,faik1,gammak1,polyfaik1])\n",
    "        dXk = np.max(np.abs(Xk1-Xk),axis=(-1,-2))\n",
    "        print(\"Iteration\",i,\"done,\",\"max dXk:\",np.max(dXk))\n",
    "        if np.all(np.greater(np.array(epsilon),dXk)):\n",
    "            break\n",
    "        rk = rk1.copy()\n",
    "        thetak = thetak1.copy()\n",
    "        faik = faik1.copy()\n",
    "        gammak = gammak1.copy()\n",
    "        polyfaik = polyfaik1.copy()\n",
    "if isok:\n",
    "    result_X = Xk1\n",
    "    result_u = u_val\n",
    "    print(\"Optimization is done\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(V(e_values.flatten(),DO_Xk[0].flatten())*np.sqrt(g0*R0)/1000,(DO_Xk[0].flatten()-1)*R0/1000,label='DO')\n",
    "plt.plot(V(e_values.flatten(),result_X[0][:,deterministic_idx].flatten())*np.sqrt(g0*R0)/1000,(rk[:,deterministic_idx].flatten()-1)*R0/1000,label='CO-PC')\n",
    "path_constrain = path_constrain_init()\n",
    "plt.plot(V(e_values.flatten(),path_constrain[:,deterministic_idx].flatten())*np.sqrt(g0*R0)/1000,(path_constrain[:,deterministic_idx].flatten()-1)*R0/1000,label='constrain')\n",
    "plt.xlabel('V/10^3(m/s)')\n",
    "plt.ylabel('H(km)')\n",
    "plt.legend()\n",
    "plt.gca().invert_xaxis()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(e_values.flatten(),np.arctan2(DO_u[1],DO_u[0])*180/np.pi,label='DO')\n",
    "plt.plot(e_values.flatten(),np.arctan2(result_u[1],result_u[0])*180/np.pi,label='CO-PC')\n",
    "plt.xlabel('e')\n",
    "plt.ylabel('v/°')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def MC(e_values,u_val,numOftest):\n",
    "    Rhodelta,CLdelta,CDdelta = np.random.randn(numOftest)*deviation_Rho,np.random.randn(numOftest)*deviation_CL,np.random.randn(numOftest)*deviation_CD\n",
    "    sigma_e = interp1d(e_values.flatten(),np.arctan2(u_val[1],u_val[0]).flatten()/np.pi*180, kind='linear',fill_value='extrapolate')\n",
    "    gammak=[np.ones_like(Rhodelta)*float(gamma0)]\n",
    "    thetak = [np.ones_like(Rhodelta)*float(theta0)]\n",
    "    faik = [np.ones_like(Rhodelta)*float(fai0)]\n",
    "    polyfaik = [np.ones_like(Rhodelta)*float(polyfai0)]\n",
    "    rk = [np.ones_like(Rhodelta)*float(r0)]\n",
    "    Vk = [np.ones_like(Rhodelta)*float(V0)]\n",
    "    ek = [np.ones_like(Rhodelta)*float(e0)]\n",
    "    tk = [np.zeros_like(Rhodelta)]\n",
    "    dt = 1/np.sqrt(R0/g0)\n",
    "    mask = rk[-1]>=rf\n",
    "    while np.any(mask):\n",
    "        dXdt_val = dXdt(rk[-1][mask],thetak[-1][mask],faik[-1][mask],gammak[-1][mask],polyfaik[-1][mask],ek[-1][mask],np.cos(sigma_e(ek[-1][mask])/180*np.pi),np.sin(sigma_e(ek[-1][mask])/180*np.pi),deterministic_idx,Rhodelta1=Rhodelta[mask],CLdelta1=CLdelta[mask],CDdelta1=CDdelta[mask])\n",
    "        rk_tmp = rk[-1].copy()\n",
    "        rk_tmp[mask] += (dt*dXdt_val[0])\n",
    "        rk.append(rk_tmp)\n",
    "        thetak_tmp = thetak[-1].copy()\n",
    "        thetak_tmp[mask] += (dt*dXdt_val[1])\n",
    "        thetak.append(thetak_tmp)\n",
    "        faik_tmp = faik[-1].copy()\n",
    "        faik_tmp[mask] += (dt*dXdt_val[2])\n",
    "        faik.append(faik_tmp)\n",
    "        gammak_tmp = gammak[-1].copy()\n",
    "        gammak_tmp[mask] += (dt*dXdt_val[3])\n",
    "        gammak.append(gammak_tmp)\n",
    "        polyfaik_tmp = polyfaik[-1].copy()\n",
    "        polyfaik_tmp[mask] += (dt*dXdt_val[4])\n",
    "        polyfaik.append(polyfaik_tmp)\n",
    "        Vk_tmp = Vk[-1].copy()\n",
    "        Vk_tmp[mask] += (dt*dXdt_val[5])\n",
    "        Vk.append(Vk_tmp)\n",
    "        ek.append((1/rk[-1]-Vk[-1]**2/2))\n",
    "        tk_tmp = tk[-1].copy()\n",
    "        tk_tmp[mask]+=dt\n",
    "        tk.append(tk_tmp)\n",
    "        mask = rk[-1]>=rf\n",
    "    rk = np.array(rk)\n",
    "    thetak = np.array(thetak)\n",
    "    faik = np.array(faik)\n",
    "    gammak = np.array(gammak)\n",
    "    polyfaik = np.array(polyfaik)\n",
    "    Vk = np.array(Vk)\n",
    "    tk = np.array(tk)\n",
    "    ek = np.array(ek)\n",
    "    return (rk,thetak,faik,gammak,polyfaik,Vk,tk,Rhodelta,CLdelta,CDdelta)\n",
    "result_rk,result_thetak,result_faik,result_gammak,result_polyfaik,result_Vk,result_tk,result_Rhodelta,result_CLdelta,result_CDdelta = MC(e_values,result_u,3000)\n",
    "DO_rk,DO_thetak,DO_faik,DO_gammak,DO_polyfaik,DO_Vk,DO_tk,DO_Rhodelta,DO_CLdelta,DO_CDdelta = MC(e_values,DO_u,3000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7Vz/nkfW/Zvm7ruPC5Vfi0lVQVpQ/lRDi+8AVwLSUcunsc7XADUA3MAi8QUqZPFF1VJQX0/ap7QykB/jkGZ+kJdDCu+59F3cfuY2rd98K04fg9d+B1lUnuprKCaYCsvKiklKy9Zab2PjLH9PQ1cMl//ZJHrcOcP36v+TAzAEMzWBN0xrO6zyP7nA3AVeAilNh6qwpjj6+mcD9w+z8wnf4zulf4+qz38G186/F7/Kf6MtSlD9nPwS+Bvz4uOf+GXhASvlZIcQ/zz7+pxNQN0V50W0Y24ChGVzYdSE+w0dHqIPSlv+FYztBM+DW98N7NoCm5jF4NVMBWXnROLbN/d/9X/Y+eC8Lzzib6NWn8de7/oG+ZB+9kV7+ZcW/sFBfSD6VpxgrIqclnqCH1rpWzu49G9+SdxC/aIQbPv1RTt+Y5BeFr/Hj/T/mn9b+Exd2XagG8ynK/4GU8hEhRPfTnn4NcM7s9z8CHkYFZOUVavPEZlY0rHiyseWSros5+Z7/wmpdibH2PXDL+2BkM3SdfoJrqpxIKiArLwrHsbn7f7/IoUfXs/Kqq3mgo5/bH3of7d52Ptz4YcxRk8O7DnOYwwAYRvWtaFkWAEII2qMtLKmZw5Unf4AHNn6Xi7ZphHLLuHviJjZ0PcD7L/wwTYGmE3aNivIK0iSlnJj9fhJ4zv9YQoi/Av4KoLOz8yWomqK8cNLlNAdnDvK+le/DdCT/79gE+eIc5pgm+9pXsXTxa+DOj8CeG1VAfpVTAVl5wTmOzW+/8RUOPbqe9svO4lOun5MeSPM279twjjkMlYZobm7mvPPOo6urC03TyGQy5MaSJI/GSI8XyFkVksU8901tJ6BrrOw6H47eT+rQPt7adC1NE11MbN/K1KIQiy5Yi6tRdbtQlBeClFIKIeTvKf828G2ANWvWPOd2ivJydGDmABLJyoaVfGVoiq8NT/O28R0A3KtXWOoOQO850P/gia2ocsKpgKy8oKSUPPj9b3HgkQfhzB4+yU9YU1zDwvhCCrkCCxYsYPny5aRSKY4cOcLDDz+MKHvxlhpxlaMYVhhBBAtJWZOYAtJSskkvEm2/iGDmcbYkf8X5K89CTPTTtt9Lev+9pOpbKK8+jUpXLwGvi7qAm9qAW3XDUJTnZ0oI0SKlnBBCtADTJ7pCivJiOJQ4BMCcmoVcv32Uyxsi/OVwHxPuen6Vy/IhKRG9Z0PfnZAchGj3Ca2vcuKogKy8oLbd8Rt233cX00u93B94jGuK1yAnJeGmMCefdDLDw8PcdNNNIKFB66Z55mTMigcHSbxOZ6hG42ipzGi+8uQxA8BpSFY4O1kb2UR9dD/a0ENIKXCMEI6MEEoG4f6fMO5EeFD28n37dEqBVpa0RThjTh0XLm6ityF44m6Mory83Qa8A/js7L+3ntjqKMqL42DiIM2BZnYVNNKWzXUtdczN9HFfaAHjrmX0p/qZ23NWdeNjG1RAfhVTAVl5wfRt2sgjP/0+Y20mB5osXhd7HVbJYuHChUxNTfHII49QU1PD6u4zSe3UyZQlBTccnuNmazGBW0xT5+RZJZJckU2wMFPHnGAH7dFdhF23AJKsdTZD1tuwZBtuguhPWy3dBVwMXIxJpZRi55DDA4dTfOvuPppbQrz5lE6uXtlKyKumjFNenYQQv6A6IK9eCDEKfJxqML5RCPEuYAh4w4mroaK8eA4lDrGwdiH3zWQI6RpnBQ30RD+F+euo+NeydXIbcxe+Ebw1MPo4nPS2E11l5QRRAVl5QYz1HeSOr/0309Ey6XntnDrehTfkRQYkhw4dItTeQf2ac9jWb3KHY1NeaVFX3ssi7xZOiR7h9aGJZx5UCkozEVIjqykk/gtpdwMabvIExDHy7jhDXsGIx89QoI6S3oDHCrEwW2BJ7ii1psOp5bmcQrXl+EhM8vAth7nmzkOsXd3GO07vZm6jalVWXl2klG9+jqLzX9KKKMpLzHRMhjPDXNB5ATen86yJBHDFD4J0aOxcg1Op4cHpzVy3SFTnQR7feaKrrJxAKiArf7LkxDi//MxHybhLsGgZHVNhfD4fqVyO2NzFDPcsYEfZgYrE21TmwvidnBN6kG59EqMomMm3MJlbRW/SR1OuE5sQXnEMWVqFKC5CoFEI95OuuYv1oQg31a5g3LuaiuZ+sg66Y+GRFXTpkNMbkKKJ1tI0Hxv4FldO9TMpLkA3LuHdlpd3mzC0Oc4NmyeZaXG44KxGLlq2CMNQqygpiqK8Uo1lx7ClTX2wh76xElc31sDkRgAWzT0ZDhTYlpvduHUVPPY/YJbA5T1hdVZOnBc1IAshPgT8JSCBvcA7pZSlF/OcykurUizww0/+PWWrjLZoFb6kFwfB3oZ29vQuZloK2lJxPjx5Gz3mXrp9Q3Rl0kQGbDy2PXuUBLD/yWNKKajI+aTtCrcKgxvr6ulqOsRFDQ+w0p0kkO/lxiMXk6sYLB0d4DWbd9Pnn8PNS85jmXuAa0NbmCOOEPc0scd3Pv/TcSbXxb7BGZXv8f2e6xmtXMgZMY23VfxoE4LxG9J846b7cFp2c8pp07Q0LCEcXkEotBTDCJyQ+6ooiqK8sIazwwDk9Q4ATo4EoO8wGF7qGubSbmxmUuthKj9FU9tJ4FgwuRc6Tj6R1VZOkBctIAsh2oAPAoullEUhxI3Am6iu4qS8AkjH4Rdf/DjWTAarewHS9DIdjrJ9xekMaS5W5Eb44sBXWZDvoxTU6E0m0B3IOh4OFjoJu1vQOZtx2UQQm0Z0EBNMaAN4tV3MN37Du8WvWZBbzjezV/Lxvo9wZtPjnNd7H6/v+DaPxHrZ0lHL5p4gutGHMHawRThsERLpBPCbeRrsX7GgVOJWb5ROvZW3TP6ASc8D/M3qf2HQ3cDVhyc4a1pwhRXGNXYWsZtsNjpTOPov8EQO4GsxqO+YR3PPSdQ3rCEQmI+mPf/+y7ZlkY4NExvfiemMogXHKRQG8LibWLz4c+j685uebqhY5v6ZDI+lclxQF+bNLXX/15dNURTlVWkwPQhAkhogxbKgDxLHINoDmsZpNQFuMnvZMrWTq1pPqu40vlMF5FepF7uLhQH4hBAm4AfGX+gTvPFbm57x3BXLW3jbad0UKzbX/2DrM8qvWd3OtWs6SOQrvO+n259R/tZTu7hyRSvjqSIfumHXM8rfva6XCxY30R/L8dFf731G+QfOm8eZ8+rZP57mE7cfeEb5P16ygNVdtWwfSvC5e/qeUf7vVy5mSWuEjUfifPXBI88o//TrljGnIcj9B6b4zoaBZ5R/6Y0raa3xcfvucX66eegZ5d9462pqA25u2jbCr7aPPqP8h+9ci8+t85NNg9yx55l9g294z2kA/Mf37uL+6XnYHUuRmoecESLreKiVZb69/5Mcnmjia+JyPPaFkIWM8OO2vXxa5AgaXXzP8bGfp06j2igb+XdqmXHN4a00MGG6iNgZKppNSEuwKRVlc0yC8FCaXIuo1CMcg4rtxsEFRh5XoA9dlIlnlxOXLg6JMmjV8xi+NayJ3MnFg//M3cl/5GZ3Dz8Lu9CdEtGyzWpL45+sFry8nr9PX0IxJbEP2EhsJH2sZiev9xTRXQYfLUcRYnaQoARbs1jsG+Ak8wCpVIGfi/OR9vHX5+Pc+WmuWmvSP/YI//bQPXg8LU+5/ifee0OJPO/5xU6SpkXKsinaDgBWd5DfNqXpsjW+cuehZ7w2r5b33rcf6eeBg0+diczr0vnRX6wF4H8eOMKjR+NPKY/63XzzbasB+H/3HGLHUPIp5S0RL19+06pnnFNRlFeG4cwQb6iFbSN302isIeIyIDEAtb0AXNrUwU3xYe6dGuKqnosh0AATu05spZUT5kULyFLKMSHE54FhoAjcK6W89+nbqVWZ/jzlEjP079iK4+vCcvtIBcNUNJ3Wcox7Hv0HsrKJARHF41TIG14cqwmXMPD7cpQ7D5B3byE3tZxyrh4cA8N2I2wfjuNFOouIFCUeY5q8KDHu1bEEIG1qhZfXxi9lYb6bW4sNxNwlHG8W0yxSSju4TYl3qpMRfxuOEQJASAeBBVoFKW2OhRrZH0mQy+UQ5lEiZS9oATLuIHe11XBfd4iT4znGDjkYlsRwNAxZnS/DJkTJNBCmwKH45P3QALftpq80B39+By2BNC4XaIYLw+3BcHnJTKewZ5ay9uRv8sCj11GpJJ4SkE0peTSV5ZZ9x3h4LImZKyKAsKHT5PMQdelcO7+Dj6TibEhmX9LXW1EU5c+dldvGukCBu2QbTeZ+shkvoeQxmFsdn3paNAzAjkwZhICmJTC1//cdUnkFE1K+OAshCSGiwM3AG4EUcBPwKynlT59rnzVr1sht27a9KPVRXlj3f+/r7LrvLnaefhkbFp+MH5MvH/wkbZM52j391Dg5hpsDTHjOhECFQu1BUlqAfSxnwF7EmLmYCb2RjO6mos8u5iEdanN9hHJbMM1tmKRxOy7W5paxunAyy/ItuIoJnIqgaJmYTrU7uxAaWqBApXUXqalh8nu9VHSDaX+UI8Ee4oFG3hF6mNP1AxyxWvlF5kwmbB+u8DFa63YxGCkx5Kn+rhiwgzTIeZjeBYyFFxMLdILQ/+D90KTk1xvyjLjhQ1GTt/j302knuWzda+mZuxTLsbj7O1/h6IaNXPu//0MpfgP9wz8gtGIjG1IlHpjJsCdXDdwtHhcX1IU5vzbMumiQgPHU869+bD/LXG7+sa2Jxa3hF/BVVf4UQojtUso1J7oeLyX1ma28nOw4cBP63f+E8Ibpve5WgtGup5T/6LdLqHEZfFD/MRc4d/EPwWMsvPMGuPyLcPK7AFi6fgPZwiBHL34Trns/Dtu+Bx8dB+0P/xxQ/rz8oc/sF7OLxQXAMSllbLYivwZOB54zICt/HjLxGLse+C0PnnU1Oxat4eTMfj6097sYFcky125iNS4e7e6k4rOI64NsMc9ns/U39HsaAPAh6S07nJp3iFayZO0BJrTHGTV2UXDVEPcuxYy+D0vvoGkmxXTsCHsnDjE98xCeSvnZKzVD9W8V1BGpLdHizbI6MMHb/TvQpKBScJHNBWlKpfnw5C0Ql0inGsyLupuRqId93YL9PQ4DbXvJGzshAU1xjYAZxe9E8ODDjRcNDSlsNDHDIB7ywo0UDv/RDPW2g89ZyQ0HVhJ2Ce6d+gAeA4RZZsmoj8XTGl//56vY+dqPsc/4PubuIXRgTSTAx3pbOL8uzKKA98kVAEumzdHpHMMzeQbjOfZP5MgfnuLhnMnDHOazr1vGm9aqv7woivLqFi9ME77lr2kzLfTsDMd+ejkL3r+32hIMZItjtLtKHPRcTrkiWVLTTGHw29WdZ7tYACz1C9ZbczmS7Gdx0xKwStV+yvVzT8RlKSfQixmQh4FThRB+ql0szgdUU8MrwO777+GedVexb+Fq3jn2a9b27WKV3ocRLLF5UQ1Zv4udcjkPWpezW1+IdGssS1r89VCJ02Zs5mZyDHrvYE/wEQZ9gmJwIaXQ6WSCbyRrhGibHGb1zs30Dt2Mq1xBAnrYwGh04YRryIZrmAg3czjSy1F/J5qU1OQSrJncw+KJQxiJEv25KIcz9YCkPpRhUXiaVc0TuFodWAw2gikRIO6EMIsG4bzGmpTgtI2S2liFWMThcJtgMuowXhsnHkqS9enMeAAhMWwbIQV+CSFHoDlg4GXaI/AGDvGloYN0T1joOaAQr46GptrndfGopM37dU65sot5U3V05ySTTZJ0+gLuONjLN5MFBmM5xlIFZgr2U+59xKvT0hzkaJukN27xnQ0DKiArivLqlhzise9dyVWVCptd51Oe4+bsQ3czuOuHdK96JwCDE3cBkPKfChVY3bQS74HZFVtre5481Fl1DTycK/Lg1FEWNy2uPjm1TwXkV6EXsw/yFiHEr4AdgAXsBL79Yp1PeWnYlsm3x2LsO+k8/m7wRywfOMz53kfpmxtirL6RjfJ87rWuZMTdTEcpyz/1H+GS2AhN5jg57SgZ9z70QAY9uJgjLW/hnrozyBkB2lMjXPvojbQOHSPkFAgZJXpqkrT4stR6Cui6JK6FiXnqSBJmJjfCutgOvOUS6UiEnfUL2Tj/FG5dfiU+u8SlsUe4sP8BmMowkoqwYWwej2hzqNSXkA0p6gLTLLAt5lWmaRd2dQhpA5jzNOJGCLc7TK3hwhZgmxJZEIiERE9JvAkTV87BMO3ZoCyrExnKLFkXvO3tPh6r3UPbsTCFbi92RxSnMUulqYxd42D5JDLnJnYkxCOJHoYy7dhHDUCicZSgdAjbggZRocMzQ3NAZ25LlPRYP+31Eequej3/8vheLmis5XsbRhmIJ7H1ON3hbly6WiFQUZRXkZHHKf/4jSxIOWTdbjYdLNEz45CI6uQ3fhFmA/JMYgMZG0ru+QAsqVtCwfIhySPCbU8e7vzGDj4xdJjHEnHeP+98EBpMH4AlV5+Iq1NOoBd1Fgsp5cepLmOqvEJs3L6Dh5afyWXD65lzbJQlHdtZ39PIPdpl3ClfT1oP8fqxe/np8H8yzzqMJqzqji4oGgFubbmEm5uvZszfSV1xhr/e9UPWTW2hjgx17gKR7ufoQiGhyU7TVEgD4CAY8Tazv3YOA5FuDoYXMOWO0lSKoeNwR+M5/Lr5ImorKS6NPcLVh++kOGVxON5AeboVR68nF00zVJtjNFACTFyyjF/aBJw8rcUsPinxHD/LRnD2q/3336N5djs7z4SzXzeNhk3BgYLl5tj0ErYeOokDmUVUcKNh0xMZZrE7QbcJp5z2bewDF5M7diZuv6BSCHDFO9fR1OVnqv8om5JHGHz8EZKbf8t7C2XGfC3QfDVX3vA+3IF9XBWcw3+s/RdE56l/6susKIry8pceI/6Ra/htsZE3rDzKMcfL6Q3DbBzrpqm1k1NmjpGMHyJav5BKoY9jZZ0sQYJ6hTq3C4M6Ku4ELiGYnY+IeQEfhizTV5Dg8kHtHDVQ71VKraSn/FE+P5FkYTbLwsERepds47GGHv6f/FcmtTa0eJH/6vsq77Z+hem0Mmpdya5KE48F23hgYYjxusXMK4/xvqFbuWxyPc0ijiYkTgBSlTDpcgfDqVZmKo3krBqKToiSDBCLREgF6/AZeYIiT4PM0SbTNJglTspanD5ZwZF92ExQllHyTpic1LFdGjmvTsJ7AQPRCzGjDmEzRTh9BDMzzFQqwbGZDIa7QGswR3sgRdSXJKQX8UiJwbMPYDURHHXXcnN4CY5W/Vi1pUNOeLkgd4DTCjl+6ArzsZEI+dwczPRyrNwikG48Ik+b3s87Nj6G0ThDy/tGmdx+HVODa2nSCrjq99MZO4skM3y3ZoTtX7+P7rFJls8cpd4sEetoYbzZoTR3Mctih1hjfIfViT564hO45Qjsexhe911Yfu0zKy7lk/3xFEVR/tzlv/9PxHb7ca2TuDQH936dVRe1sm29xcwxA60Bjjz6eVZd9gV0K85IxcWMZdDpBSEEPtOg5BGUsvuIRFYCoAlBi5Fn0qzBdExcTYthYs+JvVDlhFABWXneDmdyzJQsLurfz+lz7mWkIcK/mZ8lJ0K07TzKlxM7WOf+FSPl87k9+Vf0tQZ4fJmLet9h3hXbwFVHPkOrPQXAeDnE1sI8Jsw1TMlzyGtRbCFxhAN+G6/mENIgpGksFhphRydkRgjhwnhi7mGqfXdydhGcLLrI4DayePQUtTg4tqCci5LLNlF0BfAIQY0VBlZDYDXMLpJnOiYFK02hnKGvkKVgFSlJQdGR2EIghQNaESkKuIw0YVeMZXofnWX4dmeUos9FRdMwNY0Ha8/n7HKJinuSwqHLscrt6FoBX3g3hHeh+wZxlRpYFRtluhxAO+iiJrkeeyJO/sYoZKeZTHyacNHi+kKGoF3EX1NBtglo1lgamaLZSIO5AWogJQMcNDs46CozVvbzdm2K0i//nsn7bmdZmw3lbPUrMw7SwXnLTdhNy3Hp2jNeX0VRlD8blQLxW7dghl10uEvYEgqjfkpjBksjY2yPtzPSOkLwyP1ks/sASIsoI2WLXp8HAHehQMqjUUw+9mRABlgScDFidXAwcZTljUvgwG1QyYNbraz6aqICsvK8/c+23Zx9ZBfza3ZTbsvz2cJnyflC/MXOG3jb9BIW+H7IdGUx37f/mvFT+lhXfpR/63+UeiuFLQXD+Rruzc5lo+jlscZass0l2vQCHfJB2it1tFcaaa800VppxCvdT57XdCpUinGMzCROLk6pEMPJz2CV4ricKdKGThoPOhAol6nzFwi3loi0lvBGq108rIrGdCnKFt8atjWtYzi0AN2ooaECTSUXLQU3HdkQjRVB6Lhz/z7nleG8p62lYeHwkG8Al2sSXRunFDjGpub1FI0sUqu23p67dQq3A+2pPHxVADFaPJuYiNaze95i+k7ppSMwyVrnAItTjxNyCgD0Oy3ssuYxkQ+Tyfvoc1/EPZ56HASi7CCFhmX8ive7fsNlkxfgSugEdQu/7uASBk4pQd/XBsE1xU/etZZVndE/9S2hKIpyQpibbqAwqXN0XpiVNeNsOjlK+Wyb7JbDLGp2sy0hmCyHWW1Os3PotwA47k6Gi2XOqQ2BlIjsJE5bPYnkY3R3//WTx15X18Q9mQIPTPWzvGkxICF2CNpWn6CrVU4EFZCV56XsOGQO7qfOMemYs5eHS6czGJjHpYN38LrRk2kL3A4UuVt7HW+s+wgLh46RFV722x42jS8g5izC3TgHf2stFzh1vMWsJzDlffL4FpIJYROzS6QyI0Rm+mmc3IfITlKqZBhqaGEqGqXgc2MGBHoTtGKRkR2kZAjQkJoGmobUXQgMyEraEpOcbB+h2ZehsSHJa43f8tqZ32LFBGOOl4FADccCLQyEOthRW0/KU0/W1YAU9ehOGJMAwYpNwHTwmza+cpGWmQkWl47RaU+yJ98DdoV4w3x0obPICXNusYsHGyQuM0ZnEq4/uowlM1v5m3U2p+UsWpY6jM/tIKQXeLBhLd/ofjNl3cOiXD/Xj9/CB6c/S7BYJK5HuKXhPLY6C9k0MoerDjzK6w8/xE8uvISHV5+KDBh49iTAgaVlA9MriDMfXUhOdyfZ7SykbEnKtsQCJHX0GCMcNVv4yG17OeuSObR4XLy7veHJaeUURVH+HAz99JeA4GgozNylo5Q9BmPjGm2nOMwcDVPfn2disgatdZqpg/djNhr4/XMpOpJOrxuKSTAL6LWnkE5vx7bL6Hq1ZfmCxk4+duwQW5NpWDC7zHT8iArIrzIqICvPy539Q3THxlnQvJNKQPKTwvX4izmu2rGc1oBOQL+bw9ZJXOv5PEk7xGdrF3EoprH8cD2LOs7jImM1Fg7T5TJZyhwkSUYvkaGAlh2nbrSPpqlx3LrBSEM9B0M+KvND6KYLd7nA7IzF4BTRTA8RowCGoOw04RcCXZQQlJCOhVlyMG0BCKbQuIMF6FYQV1ynpzJClzlJg5anPlyhpTTN2cUJNG3Hc157WnMx7A6x39/Mja3X8f0FXVxy7DN8b3KardkPMJbeRa1/F1dGthMUXcSdzyACQTY31nHVlp9wyDeX01sH6SzMoTlXx6lxDzOihQ7XFj6S+SHdk+OcUt5Djz6B5WjsyS3miHYuE+VF9DfkeaB3Ho3eaW5ecjnXfupBgnUSpysAAvQGH9ZUkXlOhsucjXSI6mCSf+XbDMuFDDKfHYElDIeaOOWozoYly8i6TI4OZdk/OAW6RqPbxdVNqjVZUZQ/D9JxmN47jdvnorGuQqzRTWW4DqfrMvTBnzHWGGdBxMOj090k2weITA6zLxrAE+yGInT5PJAZBsDTsAqnuJdsbh81kWoA7vR5cMkCh0uyOgWcZkD88Am8YuVEUAFZeV42btiAX2h0Ne9lY2ktmUAdl2ybYYUvgo+b0bUyzcYRxj0N/F19F2YizkWHa1ncdjVLjXncQIFp1258eoGcrdM+M0Ikmybnr2M8EiW/ZAHBrkZapkdxWUWMYpFsuI7pth5itU3E6pqJRxvJBiNIXWdhfoDl6QFOTe3hktRD1Fi5p9TXloKM6SFWChArBZkuB5guBjlohTlIGBxJTbpMbaJAIGsRTFeoNQt4DBvH78asCaN5DXSvRPc4NHszLPQf5dqZf+fjrvew/Ojb2FmepsnRGZPgmuxgU/YqbEfjpEbJu7f6ODuXZ8r1FgJuH98xz+ay6WrrxANAQJtB+jIMRRNE3Y9QY5uMzITIPxxCUGRqXS9lX4HG0TTXTD6ChmQk0Ea5rps3bt3Lldu3s3v+Mm5eci4xHWb8GtHRC/CXz8bh3YT0SZbrE6zW7ud1QL/Zwr6a1/P6wy2sdvbz9dAVfDz9b3yj9u+4YdytArKiKH829tz3WYKZMgdP7aWpewiEYHxyMZnJMZryYdzdaVyLBUwLxq0gy3Jp7i75Ee4WKFJtQZ4ZA8DXdBoM/ph0eseTAVkIQZOeZ9oKITUDEe1RAflVSAVk5Q/KFEv4xobw16UphTVuyrwBw7C5dgJcLoHXuY0YjURkgg83/A19oxpvOLyHxlAPS93zuNk9xbh+mDljgwinSCnYwMFIPUFdoyk+SldqGImgEGwiV7MCzWjDJ5pp012cZI8QyRzBX96CTCSY8oU44u9ke3gxdzadyS/bLkJ3PsyqVIJ1U1nWTlpE8mBLiYUbt9CJBgQtQQ2X8FB2TBLlSZLlSRKVCSbLIxRCFQgBSPxIvJaBpyxxZ8voZhndMtGdMC4tSMvKFFdP3052wEtWSlyOxNfegF3Zx2KnDjHnLKSUtIT8PB49gK7nSQVylIwUBW8cyz1FhgwjQjBj6EAjAIuEh/Nb5pKNzCUvNKQ2DAgqIoLH24PjpGnPj/Pl9/4rCa+HlFsw4tcoGgII8FtgtCbPDx43KdptxMoebpt6LV3u9bR4x5lXG+dq79cw3R6GzShfl1eQSZzNitod7Jjx4AxtQismYf4loKkBfIqivDxlMns4fMetLHEkg3WdrO06RCBjks2ESHvqEZ0x9Fia6VqTiKtEPBliSV0KkhZ2b7UhoM3jgvQoAO66JfgmO0mndz7lPPN8GqN2C2P5Sdrr51e7WCivKiogK3/QnTt24bJtVtQ+RlH6GAt0s2LIZIkm0axt+EJJPAi+2/I6dg8tZ2lyBw1WlpX1p5IUOWrGt5CVcSY0h5pskoZskjpNxwm2EK1ZSzPtBFxNeHAIOAlqxQgh9xbc7hF0UQR07FKQcnEJdnkOF858gbyznwmzhUPhElvr/GxpjPKlRfWwCBambc6dtjh30qQ571ByIGFL8o6k5OhU6MJ0dyFcDlokB9oQmtyDyxmgbJUpVFw4FTeYBsJxIeTv+ufunaoGWnqeeo8OdZl8fvXNwM18aPytrMkt4Qfznrmqesh26LAcFpoBjMQ6dDvEQP1uDgYHmRtrw1MDO8PzGKlrZiocxdKr/0Wb0gleu+sRZipjFGSAxnSBFZkUteMpflCzHG8N7F/SxA5nOxfIZoLafszSZvorTeQqFTZMd3Nhbx9zjQo9nklqSlkygxP8aOwHaEjYOFvB8z8O6z78Qr+FFEVR/mQVy+G3mz+B3q8Tb6hHWmWcqIN3xOKs8y/ntvWP0ZeuZdWgjvsCi57GGAcmWzizboS5mQpbRIiADgFDh8wYCB1CzUQiJ5FIPoqU8snxGCdFojyU13hkqp/r6ufBkXvBtkBXsenVQr3Syh90cN8+8h4vnug0N2TfiIzoXDIUQ9d9eMa+SSVkYGkGX3VfQyh8J+cfG6G37nSihLgldx/l7EF0w40VbcVsW8RCq50WowW/JtCFjksIXAIMIYAw0E2edeStZ9ZlQe4gQU+SUmUdASvM4rhDbyzPpYckB8IuNjd72Neo8c1ek2/1lPCWSwRKJTxWBV2WsbUSFa1ERRQwtQJQRkgTIV0gexGygts28TplvE4Zn1PGb5XxmyY+y8RrmvgtiwOBBaxN9eGyBeZUHV1TYa5Zn6JhToJeZ5ha+3T+drIXl3aY+fYMTbZNxWrgsFzCXhZSwaAuvpas12J/TyvwDQLt03TXJ0jtdnPGrs0cnruIrtE5jNS7Mbq2IKTDtX030du8EyGh7jdwsGcBmrEYTZoA7Fmc5vz+ZkLeXSxp99Of/wtOjfwHtw1JjmY6iIYtHJGkS0yxz+7ippr5DNedhkvCB63daI9/D878kJovWVGUl53P372BldY+jGSY/jlziUQmQQhk3mH52Rdw3z33kNQ6KJVr0J0Z5IIShTEPY8LDimKZBxwXTU9MUpQZh1AzaDqRyComp26hVBrF5+sA4JzGTr4wPsqmxBTXNSwAx4TkoFpy+lVEBWTl9yqVSjA5hr+liPDA5vLp+Is2F9kp8kcfpq6rurLdrxvPp1DYyXWlPPevuZQzEksYy02Rj+8m1bwQEVxMTcXEa0wzGdzOiOMnZ7bi05LUGaOkdJOt4SSTnhy20NCkgebooAextRosI4TpCuJ2meD+CFNaL6YrRcXwY7mCOLrvaTV3IwlSMKDgd2A2QCJ0QKsuH/oncDkmfbaJxzHBdrBNiccyCWgVwhq857DO27NDTOsOR+RJ3M5CZrQgllPCp9UQ9s2nMxqmtyx588Ew1y5wUUnWsXrqNGJHHufsic14zojj9h2jEKoj0rQbMdZEsrYGq16iFSF1DbRxkI92fIHO8BjvlT/gSFeZ/P5hQkGT+9wtrBneTyJbx5LpMTzHYHfteUwtqaPDHWOrXMjB/GXYBcFQxObLMsmHM6N84KZLOYDJeZ3n8bFTP/Yn3SdFUZTfx85UsHMVXE1+hK5RcRxumU4xnc5wRTRAd2MDyXyFj/5mL48P7mN/XYSOVQX8wTrmRA8jHIlVcsgX9rF4/ny2j8eIdbTROZAg3+BgaDaJfIClMkEm00djcEn1xJlxCLUAEImcBEA6vePJgLwiUouQgxzIlWDeguo+8cMqIL+KqICs/F5bDvahScmC0HYq0iAeaGH1YIFA3oc5dBv+ZSUAfhK9lKXJffz0pHezKq3TNl5h08wWFsay7JgXoOia4EBzFNPdjKW3UxRBHA0qeiNZ9xwmAxls3YdOCFv342g+bN0P4plvUc0pollZDDuN20wQLOZwm3l8ZpFgxaS+DM0lD+3lED3lKLXUsi9ay/omH1vqdCp6tXW0tuzQXHSoK9tEKxCpQNCWBGzwWhKPIzGkoKxDSTiUtBKWkcDj3khSm4+Jn4pukZdwrOBGQ1AnLfZ1zuPjy7ys2PhJDma30uCYrPN6Mfxe9HANVjBGJbCfim+ShFZh3+hVBPQ6ttcc4d2HX8+h19vc7j6PMdpJtTwxeO4yrqm5g7Z4GrsBHAcsB5yyDqbgwKHFdDSOM17bRqr2GM0V+JuH7qSccgEQEFDRNRrTtxJpPot4o487RYR3XH8dH733YXonJ/E5ZwKDnJLwEmup4Zd9v+SqOVexrGHZS/FWUxTlVUQ6kvQdA+QeGwdAeHT8pzTzkTqLOwvVud+/PDDOx+R21o94mRg+QKX7RvYaRfauhWhpOycFswTzFprfzfDIDzj5/A+w89vfZsTopn10P665No2dSSaStaz0J2gbvRN7xcpqBfIxiHYDEAjMR9N8pDO7aW5+DQBuTSNMmlHTDXWzoTh+GLjsJbxLyomkArLye+04eJCi4SYQHOaR/NnIkM65uTHMvgcJNueoCIN+XwdTDiR6X08gn+V928Ypi0aM4a18edH1HGvpxJkXoqI/dQEOzXEwbBNLK6E7NYQLgkDJwlsu4LVi2JogF6jBX8zTPN7PothhPlxzD1vjJzFuLSPiqaHGFSWsNREiipvfzatcwSIhCsxQZELL4p2a5tzpEmt0k5GIj4lQkHggTMrrZzTkJ+/xYT/L6nKGYxO2yvQWE1yc2c9J5WOcNnwjU5Fuhpvn4OglHKPM0QOC1LjBsjeNsk2cwhc9f8P6pdvpavoZuWccFexiAH1Kw261sBfdwnh6MalCdTlT/+RSbG2GUyd2M2dsmJ7xKf77rdezx7OE+tIumv7OS+lUk/RbbT6ZPIlE3zVkKn7mixjH6jvIzgvA/gw/u6qGg6bGJcNvZ4X/f3l4oosLDgyjjadoaPUjbQ23J8T4vCjj7Z2cv/VRLAx6JzMsja+hzqjjjlvvYLBpkJaWFtasWfOCvrcURXn1yq4fIffYOIFTmvH0RCgemCH3yBjv9wgaa8dJlke5e+WZPNy/i/+d/m9+Vu/na+4azty7hPnxUW5am8FbVyaUsPC1n8pA7D4WnPGfhLFIWRHyVhQPcVzzshx5oIOLOMqKmW2MuauNBuSmob06x7GmGYRCi55cce8JnW6L/U49ZbcPT7BJzWTxKqMCsvKcHMchOXiMVJ0Xv99iQ/psdEtyQTyDObwJ/9kmLmlxR8M5mMEOdAlvuuPHzKl7O2PZ/QSMDuxVEUq9dVwc38hJO7eQmW4i6L0MmXkAp7yT9ZeMMKVJrlrfhC/nrfYnAzatOofRJecyL+fQXXHo8XWwJriMVOEtzPd7mD9bxzI5imKKhDZARZ/AdE1gesZxSKI5oFXC1JRq8ReasSp1RK1aWsa92J4SjreE8JkYngy6L4Ptz1Pxlyl6Iaf7yOh+MnqQhBZmv2cRn28+j0/Jf2B5QkcSI+4J4a64EUUPuruMVdKwDs6lpTYAXXCoshptoMKY341EQ1pxorkZgoku3O4K7bkHKYZraa0d4k2PJbl1hUPBSPG+o4ewbvk+wbkNJNuWs6HpLzhn5DA3Lz2Zs4/tpejz4R6vdtB+994Unwq7oAK1sQx7ltSRDUgAllW6mfA2MtBgc4plY+sayZpa3KkZirI65dwvH/wqLZ3z2eNpxkHHqZ3DqkCATNsaHtr7EPnpPLsmdrF9+3ai0Shz5sx56d+IiqK8olipMpn7h3EvjfKt1pvZMbKDZT0r2eI5l4/tLfO+iSY2MkHkvh/yevsBtupR7moxOD1f4MyaGSqxuazIjiM8WUI5m7vzS+mdu5vp6btYvnIVj/QNMFPfTtfwDL5oGdMxmJQe1ubGWK/b1cF2hRkINj1Zp1BoKePjNyGljRA6AEtDfvaaIbbFj3BG/XwVkF9lVEBWnlMsFkOrlGkPDiMEjHi66Y7nCBwcwJQmvoYSArg/cgozwRrWPfYoc5x63Jobe3Qbvz1zOUd6erh6/F7e9tgvyVtvZNroIl+eYlGwm4dbLAa1ES45uoJl80vovizSkvi1KOe5pvEM3I9u+tFMP45j4zVm8DDNYG+KSnCCvJGnXPZTybRQzjVi5towC0uxExFsM4C0vMDTBps90UhsAbnZL565SXj2C0AzilwQGsQdmkT3r+WeyDxc3hRUMjjuPEJPU3dymYZTSwgDWvXdtMgLOdAxxsX8ko5nnGETAGVbw00OKUFb0ARMsNUVp9VZRiVST0t5iqH6wzT3/IiisxDLMEgGQuRCfhrH8kgJxfk1FLIByFQw8tV+1uPuBmCSQtDGW/aCN8kv5ZvQOjJMZftYODjKIcsGDQb696N3dJIWfiSQdzcSLU5yySWXsDO6k1v7b2XDtRv44he/yJ49e1RAVhTlT5ZdPwLAF2p+wN2H7uOkppP42chhFoz42dy3gVObX0MgUEOXGWJjbBGyYvLG6Syr2yfZmnorySjMdW4DQMvZ/CTWyedWzGdi8tesWPclNu7cw2iog54De/Bc7OAPlEgUAiwVCdbn9kLBA0gINj5Zp3BoKaPOjykUjhEIVLtUnFbbzC8SedZPj1QD8r5fgZRqEPOrhArIynPae7QfgHbvPuJWLWV/gFXTR7BHtuJp9KJpkn5vO4cCvTRkSyzZv56Ougup2EXcmRl+u3gFkUyCrrs2sdlqRejrcQUsDJ+fvdabWN+xnxrbxwXrtoHjwsrXoUmdIjPkrRyO6cUxfVjFGqxiDWaxBstagrU7ilUKg9SfUl+hV3D5E7hD07j8SQx/Apcvie5NI6SkYkPWMZmhRAyLKSRTjiRnG2jSQHcMwkKjzVum3VumxZ+n3lfE76o85TyW5cKseKmYPiqmG7vsxXF0bNvAcQwcR6ehPslRzwKOHluLIzUcR0c6Oo6jUzHdWPk6Jis15N0V3njGd2kL6GDDYc8Eq4q9fPTay/ngSd8hQD/QTxODwGXEAxFy9QHq4ylIQrSUwNAl0jYpyRy6OUbcaMAWbmxPic2+R1k1tozTi1mO+nrINjahDwyy2lnO7RrYlUVE9k/zutx6HE1jRqslmtwKjkNvpJe8mSdRSdDV1cXw8PBL8r5TFOWVS5oOhZ3TpHpM7pq5l39e+8+8ZdFbeMtXv8JJW++jEA6zIbCbgh6CoA/8y5iT2km/ZxWDjovzan5BeubviXhLICWxiiDlMclMtKCH1+NdZFW7Wdg1pEtBvCJD09wZRgbrWRZIEBy6Bxo7q5UJNDxZr1BoKQCZ7L4nA/I5DZ1w9CC7Mmmonw+ldLXv8nHBWnnlUgFZeU77+gfIeP1EfDPcV7gCIrBuYhgnO4G3LQ/Ag3WnUHZ78O85Rsgu0ObtJJk+zL2rTyJe28T7N32DU1elceZmsQJp9hw4D0/fa5AILul7F82dO7Bq78cTjON4cpQS3ZRm5lKMz6GU7EI61f5immbiMjJo7go+XwojOgzeIiV/iUyoRClQwtZ0IiUHdzZNsTjDoF3iULnCIAUq7lK1aVgDpIZdqUM362jT3az0lugKZekITtPgSgHgSEGuGCUz085UMUKxECZbqmFKNNFWmGKJM8AN3kvwFTLMWFHmJvfRXJqmM5bk7pZzqDulg729Ye48+kYuzHu5a86NxIND9OTPIuzJs+LoWXSIg0zYXZRKQep8aciCu247kdQ6jsYXc9ehCFbcYEG/zdy3TmBoFRL+EPctqSU1P43YoWEaBZZ4/414T4W+gEXtxK/YFVlAQZOcPHCY6fFFwCSTQETsR7qq7eJ2MonW4DAm57I8NkzKL9Adh935RubaZchO0BOpTvZ8LHOMzs5ODh06RC6XIxgMvrRvREVRXjGKh2aQJZufuW5lXnQeb1rwJu657z7m7NpKOlJLXZtOUoYIDR+GcplSdy/9dSfhSJCVMr811rKw9jcYoRSeomTEcNFY/1vu2LOA15wJsdg9LFy0mM1D4yTDnbTm9uFqLtC/twcHqJl8HHJXVytzXND1++egaV6y2X20NFfLG70e3E6O/iLQPa+6YaxPBeRXCRWQlWflOA7J0RFStQEi/jK70ysxLIdl2/qRQkPv0dCRPFKzGn/ZpL1/LxF3I17dT3pyP7dcdzlt2XEu772HRKPBVKKd/t++j9pcNxLJWM1euhc9QGvHATKZemKji/B484TqjhJu3wWA7QhiJT8JW2BXCriSFfZ5G3EKDZTKQXIC0hQp5hIkbIeKnkcgwQt4QXc8NKQMVo9azI1ZdCJp8Du4WyVmdwGnYejJ2d7yxSCZZAMD2Tlks3Ukc/VMGnVM+WuYdteQtjxkgz6shTW85ZFf8o88xGfSr0GXdbjMRrT8FvRyFq1U4JrQrex3NfOQWMkHQxp9WTenOyFu8k7zV4mf4hvROeSspD5r0ezMYBWCBMMJwjNhikdToEETLtb+rIXlMwOYuiB9hqS+O0bG5yEbcLGzMQsCNAma5cOTbaRrMsCxedP05eNYbgMtpLH+pBpgjEv3RSiZFkWn+qfBVZVxmpwkLWKYX8/dR7Ll3/mrTXcxlJ8d6JidoCvaBcBQeog1TdUBerFYTAVkRVH+z4p74jgBwV3yQT6+8D8YvX0/k1uGCNg2WusSsk6eSH4CJ58BQItPQ0sPSIln6Cjl7nmMuzzMq0kRLFrsdlqJBQd5bPJK3mx0Mx27h2WnfZath3/EtK+VnkMHsBZbVBydmHTTmhzCyk5Ww0/gd0FX0wxCwUVkM08dqNek55muBJB1c6sd9maOQM+6l+x+KSeOCsjKs5qenkZUyjT7JwAYd3cxJ5VEGz6AHW6hJrQTE53HIisJjhboKR2j2Vf9DXsooDPZ1M4HEt8k0WggDl/F3iPLac234yCpmX6U3ef+kgsayoyNLeCXo5dwZS7KAhnke/4dRFxpOv1ZIuE4oVCcecEkrpADdQY9JMjaSVKWIGMLKhaYJYOoLBNxbIq6m0OBFoS7gYjhJtyVpYFp6sk8eW0FyyCbqSM70kA2W082W0/B9DJj+BjVI4xRQ9L2Iws6IiMwsPGKHG3uONJOEkrlyBfdXO3ajK+SAqFRKWs4UmcyUoN/wk04WIROeLAwSrvVTv3+Zbx9/1YY9+OKlVlsfI/R1tNBs7DytbjqJplfDjJZm4MUtKCxrXUu6TqTrMfN0uQ0Db0x4kYbq8fcfOinNpnzLUpX2Pzn/o8xMhWCfBzHvZ9c6W7KHp2gabFvfg+B9B6Cg90UEjFK0sI0/PiyOrWNabKaH+EkADAjIbKxMg4CLTNOfesqDGEwWZikfk49APF4nJ6epy0jqCiK8jxIR1I6kuJo4xgel5ezx1eRfmyQfcYEwe6FjNseWkWFciyFWw9xub2IW3xxsCpougurtgXP5DDpzrl4ImUC4xZ6ai1O8wbqoo8xPOChvnM/NYsDeCpFMu56SmMa+hqHQFOZZMnPMi3N1NQe2gCCDU+pXyi8lImJXyOlg5htPZnj1xlxmhk33LQZPogffelvnHJCqICsPKvhkeo69R2u/aTsCCV/gFWTR5C5Kbxtteia5PHIEvKuAM7IGI3FGM2R88gXp/jN6uUYjsmSmseIji7jm0PLWJHvIudKEaiEKEV/zWuiNplMPXFXlAu7hrlw90oeFiZbek7h781v0drWx/bhddwdv5KOPVO0uafQg0UCgRQebw6fp0CNN4/bV8IVNNE0AB2w6WIU056gUPZQqfiolIMM5NooFWooFCLkiiESuIk5QabtMNN2hMLsFHGGY9GbHmdN5hAd2Wk6ctO052LUFdP47N/1RR6mnst55Cn3bEdXE1mvmzP3HyFdbIJzTyOUH6M2ZVLy1nLOthRlt5uCz4urkmDh0dsZ7LyQfLYdOECn28MOIwUp6HZMtjd2Eq8N05meT6m4gwZtmgH/fCzNi7ANPClJWdi0mwlGCJF1+wmXGygAMy6HbruAbTSBkOQDAUjEwM5T8taSn67gnVsiLULMGTZJtEExHMQTm2GGKA3ZSXRNp9HfyGR+klAohMvlYmZm5iV49ymK8kpUGc0iSxb36Y9yVs05DNzdz48ZoM5ls748lyX6GHbFRCsVOKvmMvLbfkBx4aX4Z2JIaVOsb8admcZPDE2XeIsOjbnF6LkRUjX7eGD4fN7Y2cfMzP10tbdzKF0gpjXQwATeOWUmDtWw0JdifHwb6B7whJ9Sv1BoKaOjP5kdqFcdkHxSpIaH8waPxAZ4c92cagvyy4SUkryZJ+AKPLlEtvLCUQFZeVYHhoYoGm4a3FM8VjgHwrB64BgA5WgKHZsNNasJFsq0JEZxCZ16Txup8U08evE5rK08TlTLUeh7J/Oygph/lPpCG6GZjYxeo9NrWOzvW0rp6BRdZjuucIKfz3M4e/g+XCv7SB0NE8lobFnZg6fpEP+98yfcOt1JbKSduCtCIjKPgr8GTTMwELiFhaY5SKkjpcCRghIuStIgL92kpY+U9JJ2fCSkHxsNcGgqTXN2YhtLU4PMTUzQmohjODYAtqaRrAmSbTQYqAlTDMHDjVcQ0Kf57PSP+U7TaykeGSHrbcWRHmpyExhOhb7FTSRWV9AdydiS89CcUbx2C9e+9m/p6biN1dNrqR2f4cJH7ieUHSGRrq7iVGtA1rJxtDJdssI208uepafTsNMmWVlAPUfJe/ykAg1sOOMLBBt208Y3aGAU6KKge+nK+SkEYErXWCILCL0GgKTPj5vq9G8ldwhfeZKwXWLcaOLqfg+71+ZJhwLUAJOiiYZs9S8HzYFmJvOTaJpGNBolmUy+dG9CRVH+bA0NpNi2ZYLpgTR2vIAol/FKmyZXgMX7DRrq7yJ+7p00bHktOanjcxLUuwu4kzF0IXCm9hBvi4IQjNaadB6ZwhWOIhs6CNoHAZgutJFyIiyYPoMDvT+jX/PgduqZjv2Wpavfy6H7HiIR6KJlbJJgU4aBx+s5t2kQV+JYtR/x00JlOFRdFCmb3fdkQD67oZMvjo+zOTHNm+vmwsTul/ZGPocHhh/gs1s/y2R+ku5wNx9a/SHO6zzvRFfrFUUFZOVZjY+OMRMJEwmX2JddBlKyeMchHF8UT3sSAWyJLEebLDHX6qPW3YKhuTgYsCn4AqyRj9JytItvMMZcayGmVmJSN/nB3Dn8ZzRPYqaV827cTTCfB/opcBv/sSHMofpWtu47i76mCEN1Xly772fEkvy3+UbuDHqZWOpGOm6k4wHHjbQCYEZw7BC6NJDVXsg4CLxGkZA7S407S8QTo1ebYXlikO7xJDVjZQKTJbyFMlANw+mGENMnRbDnlTHmp5ENDg5lyuUgsVITE1YrGwNrqY8lcfN9aDdYvMtNs7vEJrkWi2HQBG3TcVxtHurLklIwTCFaIBjXkHYHZV3iIkMmWoOle/CWEpRmenAcQdBtk8PB8qRptSym/bXUp9MIo5VStpn62enhUkEfK3c9QixS7dLSolW7j0hNoyYrGQ6FGBfVJcDrzQplIGlodOsmRdtN2R0gkjWpLdjMeEI0mw5GucSEWU8XMGO0QHYSgKZAE3tjewEIh8NkMr/rqqIoinK8iuVw071HObJhgoakjURi62ksVwnpgbBZz6jpYMsrKDy2FiH2kROSn118Fb3xcTiUICc0QsLDJvcQtfMbCJBnvnaEeGgVdnycQlsvYaqDt3cXVjBWc5BTY2dysPtGXJGdDI+EaNZ2Mm/FXIxbbyURakM/KoickWfYbqOATqiYRjZ1Pn0SUPz+XoRwk80doJnqinora+pBjnAwV4D6eXDwNrDKYHhe4rv7Ow+PPMyHH/4wC6ILeMP8N3D34N387UN/y2fWfYYreq84YfV6pVEBWXmGcrlMOZXA6DbQdMmw1k1DLo9/5DBW/VzqQkNYaOwML8Q6lKOpNEq9dzkAD81pw5Amq+ydMPoWGnMNTAaPIQod3BAqcVbnBnwuk+y2Wu5aFCcWuopWGYZUPx3xMRbHx1g3cggAS2gMh5sYCLcwGGmhOdCI5o+Q8oewdDeeSp66Yo6m/Ahhs0Chvg6trY35AlZmJ2ieiaFlRihmx6mk0kTiBXSn2oqaC/hJtEQotwtkTwmtLUOhWCJBLeN6L8fEXPaZKxj1duPVS5x3cBNXbrifA5ccZaSphTRBGswkN77uQj6x/1a0md/1ZbOLOu5gmoayZNoj6PSOAwuIOhoxs4tEXYRQzCEb6sRXmMYqRrEsDwF3mbItKXlmqLWjJL1B5ieHiQVr6YyHqDOT4Iac10vP0I+pRK4DoE7PPNG7BH+uiGU0MaZVW4DrzSxjQEq3iLhKFG03Fa+G28wRNSQV3OgugcfMkHTaQUJc1MNxLcj3D92PIx0ikQgTExMvzZtQUZSXNTuVInPffZT27KUyM8ORgovH3acQ1pqI6mWyoRFM9wTRxCT+6TTSfTLrmtqJRXYw2PQ4049fx7HGi/jpuWHmD+xn7fARii43N1z+dr66/kGmxx5kgE6Cdobr9J38pNbGOlaLU5MjFZyLVTrEsNXFCt8djMycR31iOVO1u9k0cT6v7TpGobITH3GyzCOZ9eI3CvgbS8QrXprcebKeAOGnXZOmuQgG5pHLHnryOc/sktMjpgsa54F0IHEMGhe+tDd8VqqU4t8f/XcWRBfww0t+iN/l5/ol1/OOe97B13Z+jct7LlfdLV4gKiArzzA+Po4AuuQ+JJDx1bFuqh+sEkJUCOhFDgTnUJEevOkYdbkC9U1tFAtTPHpqL0vlHrqm8nzeP82K6dOIBSZ5SCthCJsrajdTKgXYbfSyZd1lXNvfyiUiwsWvPYvrDvwQb0eMPetPwZuyieTy1KRSnBnbzwUjO55SR6lBRdNxDBdS+DDMIpqsoDkSTcqnbGt4PBTCYY7Or2dvh2BvR5HliTJtYzpjxTqO5eYzUJzPsY55lLx+AGpSM5yxZQvXjN3PhVs24q+UKbl06kmwsWE12cM1NFSSzC2F8WtJhPa7mR1sS6AFkzSkHAYDGr2FGtJAyBHMlD3saV7EGTMHyIRbiKT7QYJjG7jdJYyCQcI7RSRXXeEpkMyQbnMAg9pcGWqh4PZS8nmpmRrCsdwEXCWkoSFsB1epgm00MDL7X7vWjDPpeMkaRSLuMpMlsFzV+aN7A9XV+Cy3C18pS8ErENIgIUOQrbYaN/mbMB2TZClJOBwmn89jWRaGoT46FOXVyE6liH/jmyR//nOkaeKEIwwE5zPe/TpCWpB8YAip9dE0Psa9K1bRmp5kVbGdWsdAaoL/7XbxQO01LLAmmGwMUZOtcNkDNyF7V1EppvBbDn9/7qV8dcMWRgw3hZjJTdF1XOfZyG9cF9I/M0ExMI/keDeGNBFWF6ORQ6yZOoW767czoFlo0kMsfi/RugmylXlMGW30cIRwV4HpwQidtXlG7fIzAjJAMLSIePyhpzzX7jLps2sxo6Fq2/XMkRMWkL+x+xtkKhm+c9F38LuqP69cuovXznstn9j0CQYzg09O0an8adRPOeUZhkarA/TatAGGKl3YHoPlo9X+xxl3HA14PLwUb6bMYnsQDaj3tHG0eISZyFyuktsoxLrw5psp60Vi+S6SPp23VtYTasgxMTCP3y5ZQzzYw9pjJlt8kHVrLGt/HN2wqY0fwzUnzyfX/icLY4/xupHDTBdqsPMuAsUSgXweT7mMyzQxTAtNOthaGEfTsAyDkteLFALNsdH1CgZ5CtJiSgjMnMN4oMTBpjz6ksVMNb8LafjxF7KctH8bZx3cxqKxozSMZfCZNqauc7B7LguCw4xVbPzhUTA0skSoN5OMeX0E9CRCGEiq6/ZVDAOtYFFbMtla66Mn77ALqJU2Ryq1xHzVD7VsIIwmHTzlFLbtwuMp4LOCzBhxWhwfYOItlBj1V/+bRrMa1ELR7aHk9eIvjJEtRvB5Ski3hig76CUT22hgmGoIrqtMoVNDwZ0mMPu/vWRUWxdKsQQ0QdHrwp/LMx7R0GwvadsLhXh1f18dAIlSgnC4+uMkk8lQW1v7Yr4FFUV5Gco/9hhj//RP2DMJQq95Dbd2n8Z9xzycl9aRWol88HFW7XoICqNECpJTtm+b7cYgCZ50Gv+44lQeajqDubFRBlsXkgsGOWX3Lgw0coakZmycL3z5k3z1TX/JR0/5Fy7e9SA1mRkekotYW9/H6radDA8uRvMmGJlaTIc1xAFjPp66X9M48FHclTCV8EFS0yE012PUdpqMHKyQ9HYxb+wogcYs/XvqWFM7TroYf9ZrDAYXMjHxK8rlGB5P9S+Di4I+Gsd8TPyghKf8RRqm+tEWvWS3/UmJUoKbj9zMa+a+hgW1C55StrZ5LQDbprapgPwCUQFZeYa+oWHSvgC1wQy3lS8ADyzbfxQZaER0FzGweTyylPJUmXrnECFXHR7dx85aNwAnF3fyfb2G+TMr6a/v5/FyF61amnN9D4CAqZzgrff/gpH6dTSHTucnjTpd0yNEG6bZP3Q6m1efSXfjHiZCbSzPb+JatnNfrpfdM22UdYMZjwvp9yG14JODLIR0EJaFsC1EpUBdvkhrKkdDJo/PrA66M3Wd8YYm5qQ7MUUcnE34y1tpTntoTJvo1uwsFYYHp3YuBwNlhgIaR3oXsGRoDnObouyzxgBIizq6KweJRzz4tRQAjhDoUlJ26fgzgmilRN7lx3B5scwK9VLiVBrIGwUAMqFqUPYXp7EtFz5/Gp9dz4yRwuP4cGGil00yARdg4ysGcMkyBbeXotdLY3KaZDmMy1NCenTIWmBKHKOBhF6doqi+Eke6o+Tdabyzrb5Zd7VMJKeqAdlwEcoXKboFmuWn4Mri5BNojkOdtxqQZ0ozNISrPyxUQFaUVxcpJTPf+S6xL30Jd28voS99jb98NEHtGFyYklj6JJHMA6zbuB1fuYzUJBaCZKOH2nkFOpsS/KrldB5qcvGevjvouW8ft595HluXrWDB4Y0kWnponpnhnK07cdkOX/jCv/HDy6/h0TUnc9nRIXoTh/is/xq+Efw6HTUuzM59HD58Fh5ziIrLwxmVPNvcWTpnVjLQvJHtEydzbtNDBJtA35GmEKpHHtPwn1JiqBJESrAKMaSUz+iOEApWk28udxCPpwEpJW8+7Kd7V5GCX6LJ+RT6Hid4zkv/OtzYdyNlu8w7Fr/jKc+bjqQj2IHP8NGf6n/pK/YKpQKy8gzTY+Mkg0G8EZOD2UUYlk3Pvt2Y9fNoqNsJwPbwEsTBMrXFGeo91WU5t7ZHqZMxemZGGLK7WOJ4mLYDlITGGmscc5HELIQpudJorgiN3vkAPNLp5uSxPdAAQzNz2Lp4GQ/6TgEglEkBkOy8ikV6I/XTQ9ilQxwwk5hunfpQgYJtUHF0So5BETfJaD2HexsZb+pkvKkdXbhYMnCEnrFhFg4P0DU9TaRYAYLEAyVioQL9rV7aC024g0uIXBJH6j7qt5/LFs9B5gztY6N0scq4hFWZ6uCQmB5hTSVB0i34x8YIrTN5HE1Ht0zKhk4wDWGjANSSDkQwywVqHA/SjGJUJrGFIFtTnVoumBvFNH1omkOtdBPXqwPsahFYlkYi6AEKyEodNaQout2UAl6MxCROsQlXMAGzodcxwTbqyWgaDtBcTmH55pJ3T+LSq4G8pFV/YVgbKQFQ0bxEckWkJpAEkAgKeAiWUk8G5EQxwZxwdVS3GqinKK8e0raZ+vRnSP7sZ4Qvv5w9f/FBPnTLQc4xvSybtvGUdrKi79fUJROk2n3Ez9TJTDWx3HuMpeFqd728ZpCt2cYb4jPcX3M6H5/6DY8v+RB6osRh2UvM287n1n8dU9N4fOHFLBw7yvV3/op4TQ3xBSto2hujbmaKh3wrOKX1cQ43uRk+kmNab0OzyiSYz3D9YyyZWcXRlkfYY3k4V4LQoaDP4BYNHCs30OmaxFVfJm+5qa2UnrU7QvC4gFwbXUfqlqN07yxyc7uLnauG+Ow9XkpTEWYyQ7QEWnDr7hfsXg9lhnh07FEkkrPazqIj3PG710FKbj16K6e0nEJvTS8AA4Uyf983zKZUnjaPi2Dd1RxVAfkFowKy8hT5fB67mCdSm0FoMGm00Z2Oo5dzOB4f9a40k+46xvUG6krjNGZM6mvaqJh59nS2cBJb2FYM0JVcSkUr0W9GqdPzXLr3IfQLC0xMdFMzYDLt8XKyq4ZhHCb8BvPD+8hma2neMcmNez7Ap65/O5utZSwsxnGAf15zMYVT/MAZREplPLkEmq3R5hKgpRnVo5RdXtIeP3J2gneX7TA3VaYjXqKpuIQauYxUe5ls8yDFwk4q1jjtM2mmIkluXqeTCM0QKG3iVH+ZxeEKHn018dUL2DJvCdfceyMbY7eTcAWBixkMmHjTJo6ryEa/jzfqGaTuBcuk7DLQsoJQOAdAxhvGVUwS8LYgrTB1+jZynkY8AYFE4CvEKJWqfZhrNY0Zrbpfu1WiKN1kfG4ccphmE2HSlNxByl5PdRm9vAu9PodLBwdJ2dZw9ChSCIq6QVsph+WKUDJySK0eqFChGpC9+RQAZeEjUKy2aluiGqIzBAnm49SFq32hZ0ozBJoDABQKhRf5XagoysuBdBwmPvox0rfeSuT66/n31Vfw0M0HubripTdu05i+FSt5H7evNtjT28WZA0Xekhukq3HkyRnUxhs9HJ4bZJFxP4uA11nfZtf7T6PiGER2pdkTXsqlA1upzaX5wtpraRLHyC44i+WDGT54ww/5pw//F639i4jm9vLDzLl8uftrCOHCXxwl4V2InprhaKSb+f5fo49fiKcSohjsp5zz4wkVOBacYIFcyFF9MZ1M0tieZmIqSKc7wU+GN/GXy54akF2uCB5PC9nsIdJ3DJDfOknw7HY+556ks2QhwgnKiXqu+PXlrGxcxY8u/RHa7M+ceMUibVnM8Xuf3/0t5sj+8FMUtm/hR70Zft5Wps6yaLAdvu+P8PPX3k5ToPoZvDu2m9HcKO9d8V4AJsoVXr/rKGXH4QOdjWxO5dnhvogLhr6IvOV9iO6zYPkbmV0kQPk/UAFZeYqpqSkA5ti7cBDkvBHOmqgOkMvbeTzC4rHQItwFkzZ9Et0yibob6RMxcp5mllf2cqPm58LkEoYjU8RlI6fq49TWDpLTHY5VDIIxnbhnAcvQudcPmuMwv2EfsaF5NNadjt6WI0WU5uI2FlQqJJwwZ++4hb5W6CitwSwVmAp4kb5GLBFGd2qZV3EIZwStJZPWgoVhTlC0D9HvGaDPN8je7hRn2itYOLUGy7UALbwQn5VhKjCCbU9y7XYHf/JeHjktysPeKR4oedGWfxdvKUA62My9a6fJ+SHujwEwGi5AGsKU+elQhttkhnHND2QpGzokNcKB6pzBWU8Q2xjD41SnmvAVMiT9c6nJJym7w/hKM8Tz1S4LdZpgWlQDaCclhjUfaBpl3cKsRKkhxYi7lrLbi8BBywl0Tw6PsCgiyEkPzuzcxzlDo7lcpOwKo+smeVcQSCCpYBo+3MUyHlmhKAL4inkASoYPL5AlCIU4ofq5GMIgUUrg9XoRQpDP51+S96KiKCeOlJLJT3yC9K234nrf+3hN/VoyW8d5c8FDc8rE0n7Gd9Y+TjxksOZIDf91bIiT6qotxtmyTmIoRNrjIn6W5IBcwmbzTN4yfTtNRoYtDWvw7p1BSoe/tTazevARpkJRHmxZg3CfzLXjt1E87VQuufs+/urG7/LwVX9F56NHmZfoY8fcbiAFiRRGQwVDaJSEzoJcGxtCI/QkVnCkcRN7hxezauFOUvVlGC9T9nagTei42mz6j9YxL5Tgob138K6lb372bha7QuT2jRM8s42aS3uof/go8fQxtlqjrJJv4c21F/KL2P08Pvk4K5tO5r+PTfKdkRhlKflCa4Q3z+tC+z3htHJgK2PveSelmMPPzhE83CT46dEEy/Tq539JTHH419fTdN1toLu4Y+AOvLqX8zvPR0rJP/aNkjJt7lw9j8VBH47j8Oi3LmHd1BYqE2Hcu34OAw/B1d9UIfn/SAVk5SkmZwNys2eE/vIcpFdn/uAQwhMiHYrhocy+4DzMGZMa5yAaGmF3PTsi1em/lmd28kClhYBZw5CRR5iSxYUCmVUupG2RJ4ft9eINLMZAsKUF5sYHCDQU6J9sYE3ZpthW4Bhz6Kzcw8KKiVeu4r8SV0J1RWT27v0KB4IlXtP5fvz6FBVRol+zCDs+WmQUgBnNx6Sri7Z8lEunWmieTBLM5al49nK422SyZgH+rJdSZSEWSwAoNl/IyQOSFSNJJiJDTPrHGK5LkvIU0KVGsNJOS97kwU6LeOVM4GHC5Ak4IYIihiYiIKYpugxIakTaqqvOZdx+zICJO69VZ6woaGS9fqQWo+yJ4q6kMbPVbipRDfq06tzMLZjsdVVbliu6Q7FYQ4QYh1w+Sh4PwnYwMg5CcwjLPEXcpLwh/CWJQCdtCOoKZWxXdXBdzBVAE3Ecp0LFFcJbyhB1suSNIP5Sta4FtxevU21BJh9HExpRb5SZ4gyaphEIBFRAVpRXOCkl05//PKlf3kD5rW/nCn0ZvrEC75yBULHEzubvsaXnEMsHwrx5v8E1TQcJ1VUo53VGN9dSibnI1urkP+wlP7WYR/T30ZiYYGrofBY7Z3NglRumUlzW9TALfQ9Rd2eFfXO6eFNgAz8zz+Pmxiu40nWAoz2XsvTQzdw/cYDW9nomBkfoJ8ocmaSmXKSSjJGvb0GvFJlydRMxssybWcmh5o0cKYYoPnodpwC4IGg7jNpzaWk+zLFiFwALknvZkSmwOhJ4yvWHpk7DvW8e+lwfkcuqLcwN5e1Mpm4kHl0LafhA7Wu4KfUw68e38YnxKNszBRYPH2a4sZ3PHZyhfvAwF1988bPeX2v4CMPveAd2WdJ/aYXtnRF+dWSKBk+RTbEOpstB2loSrOl/DDZ/A+f093Pf0H2c3XE2QXeQRxJZ7pvJ8O9zWlkc9AGg7fgR66a28Omu69i5/APclL0dHv401M+Hsz7yor1XXslUQFaeYmBsnILLQzhU4IHSKvDCgkMDODWdBNrG0YB9wXloR0pES5OEXHXowmBHS4gmOUGikKQjdS4Ag5UQrXqaJUf6cNZVSKWaqClmEVaAWk8TppSs7/BzbuwQluliZroW48hPGbq8SEEE8JSP0mFZHMr4+eqc79KajbCu3mF6TxbddrOH3/A67y/ZpK9kg30uQ6FT8EfyLEoWWRK36SkE8RmtiJrlUFO9Ph9wMuDYNpYvS8aVpL84SaJQoHVimnQgTKIhwKq6JLnJVaRcCb6w4GzecMMXuGb+HXyi2MzjSwtMuJsBCMsclowS0lMY1CE5QtllQMYgaFRbm5NunQA2AoFPQqnkoxDygnAoeWuoSQ9gZlsACOoOaaqDBes1ScYVwFsuUTYkhVKICEcouHwUPT6EKTHS1anaGq0MU9ST8QSJ5HM4IkBKF8x1Sjh6NSDHNQ8uzaFsm5iuIHY5Q42TJ0OQ2uIIAHmPl9oCZEXgKTNZJErV305UQFaUV76Zb36TxPe+T/Kq13GdsZrassP1I2WEbXPHgm9R0Id58yOtrDHiXNC2HyFhfFuE9NEAck4PidWX0uCfS+u26i/4J2EBDcD5WELSfrhIQUDblmP4tBpgmvBFLt6XvIPx1lY2jMzlAXMeJxV+Tjw6l3fecROf/9CnuGT8c4TcSVwlyYqaSe6dqUM2tIJpMuZqZnniLsbk+/FVfGStAyzbncBdqbBt2XKE1006VU9rex9WjSQvdVYV4tw3NcjqyJInr3184170B3qIlUd59JFbePPyD7OjqcjU5M8xPQtZHL4UBkGMJ+gOL+Rb8W5KRpZLtj9M78wk+zIJNi5ey8bN93DOOefg8Tx1QRHpOIy99y1U8rBlfgs3tuT57FCKpkiefdtb6J6bJG+5WX94Pt6lWZbs+in75p9DopTg3I7qz9avDk/R5DZ4V3t99aCVAjz0aVLNS/hOtBMrW6G87iN4Ygfh4c/CoqugYf6L/r55pVEBWXmK8YlJ0v4ARsTmaHYewpH0HDmA1XkKtcHDABwI9FKbKdOatoi6G5HA/uYoy3icu+0A89ILmPHGSYgAZ2hJupPbSUXKjA0HCCUsxqxW1goPo0hyHoOe8BFS6SZyFQ/+xiwDoXnglGjOV7soJEd38shJAV6zL8L05jZyHkGeIMlyjsSYn+I8HyC5+KFvs2DkGN5ytQU23hkivcSgT5xD++IjNNaPU6y4iaXrGZtupbOU4FIeZFkwzw+nLqA2WSSSzKOdbtOwchy5S6OuPAOcTdZjYHgdPDFBpJJl2lftEhFxcqRkM2E9iS7mYgGmrqFlNFy+BCFTknALIk71/vqloFT2YdRX+6iVvCFc8QJ2sRnb1vEaNgVbYht5aixByhMknM1QdEExHyZCCik0UqEwWkXgSpWxgRY7xV7qybj8NOUyzLhDzGg6KyjhaCEAEppBg2ZRtg0qriBOGaJOkRRhvE4KgIJPIPIaBeGDfLVVudZbqwKyorxKJH78Y2Jf+R/Gz7mQv/CfwSpXhov7vZSFya+XfYPOqRIXHO3iwrrDLI9OUkoZDD9Yh1O7Annpmwh7GnFhUwjs5ZhxjIO5ZnyZNO0FDyvrzuWwnuFIQXA5Li6seTPW1i+RqI0i5g9wzPHzxr0PUwj5eTzdxjeXXMZX7v8mPrPIgm0PMt17ObXBH2BlXSwMx3h4ykQk4hTCNUihEWwt02cN0ZVcSV/L4yRXl1i1qZ9LH5jmnssvI5eojrGobc8yk/SzwlXkO0fuYnTPPdyVqGNkJsv1iQWYUrKtWIP0vIFH//Gf2TEvhfvsLt6XegsNUyXAIntwnMMrLiXvauGN991I2+hRtEqJNRODHG5sZzIQ5pvf/Cbvfe97nxKSB/7736kMZNnfVs++VTle1+9iRcsU/TNR9EHwz2/i7LZx9qSbOViKsDTWx9b+u9GExpltZ3IwV2RDMse/9tTjeaLrxO6fQ36a9CWfwDh0P0UJhwtlll36Oeh/EO76e3j7bc9YWlv5/VTHFOVJtm1TSM7gdyUQOkxo7bRkE7jNMlLTiBp5UnqQSa2eVj2Lr2BS42lizG2R8gaZVznCIeGiPtfFiK/astlbNjHnVmdLGDUlqayLuK+D+WgMeKv/WXtDfaRTLZglidaaYJAe3OWjLKiYANzbXZ3Ror7ip3lymJLbIKeFOP3eHSSPBpgW9YRLGdrjRWqvupJvX+njt196A4tvvBffaz5KKuBmPBtmS986Nu09m6PDS6itW0TH5X/L31zwM7Ya81lTP0zFHUSTDlbCREowvGnCxep1pAN+pA0B0yBSSREPVGd3aDCTHHT1EtYSaLOLhUhNIPMgAymiFUnSLXA71YQclhZly0ve/URADqJJC5Fz4zgGHsOiIsFyZ4gIg4ruIpLOUvIILNugppwFIBmKAOBJVvurNc8uLV0wvESzGRythpiu4xFl3LPhPK2BT6/eU9PlhbJNjSwxQwivp4BhlSkFJEIapAn9rgXZW8dMsRqWVUBWlFeu1M03M/XpzzC0+nTeW3cu7wlu5pKjHgpant8s/h9O2+/hzCMe3tq+g+XRSeKHAtw1uozhK/+B4KkfxHa7eDz5AHcNfoU7Dq3n0SMxyv2PkZ/czWjhMLsSD3G3J0cFmJvdgw83vmSORGML83ecjqPb+FYOcLJrH3PCSUY9Lfxo2QUU3Aavf/AeNvYswxO2SKd8uDSbuaEcMpvAcbkQlsmUM4eB2vuYM7MSW7N4INhE6XybSDaLK5+jaAco5COEWvOMZ2votCze++1fkv3X77Luq1/j+sl2EB425XX8qUE0Pcpw++lcvrvIJ0U98+f9PQNnfgxHS5IvuVl9NMfbHr6d1tF+XD4fctEyCr1LuOjA4yT9IfoKB/nbOz7ILX2/5cv3HeLCT91I7MZbSPg9mK/7/+y9d6Ak6Vnd/XvfytX59s1pctycd6VVWmUJJZCMLMAEI2GwEZ9tskkfBn9GxjYG22AhoiSEUEIB5bhBu6vNYXbizszNuXN15Xq/P6pndqVFYiUjEFKff2b3Vt+uvtVVT50673me06UbWbykssTZ8QKnXuiy9rsx97+wxdrBKWqViFazCsDmmY9zxdgVFHWT3z/2QTQSZs++koce/jGCYBXu/3OYuIzy/hejR4sAPNLzoTgOz/sPcO7WnCgP8XVhqCAPcRE7OzuQZeyJHwagbde4bO0xAFaVYl6EHCvuBy+hqJ0DlVA1x7nX7gE1ZnuPMerNYWQWq8piRHjs3mjRvdwiSzI8vUOh7VIu7UNH8PBISq3fZNTZYrF5A+M7W/gHFOey/dT9RzgURniZxfFaip4IDrxmgSXvZmCDsFLBfGWPtFxhIxklciw+/ZIbAagUXknrbvidu3/n4t/W7c5RLK0yfbDFddd+DwcOvA4hJFclKf/f8Z/mRe/6PUKrSLnT5+7pNq9SEt3qUAzywI1muUISaBQTjXLSICkfpiOKjEUNzphXsD/4EsgnfGxZJFHFFvUwY8cSFLOEHlAlYzm1MY18kkRg5/4xvR+QphqmEZL1NRKrRSmogoJSq03fdlEKakEINvScAommYbV8+sCYzAmyEpJCzyOeqrEx6KyuxR4R0JUZ7oAgR6aBiGJqyqehyphOhB14BK6JyAw6skDa20JjqCAPMcR3Ajof/wRrv/wrnD90Be+c38+H3N/k9rM/Q0fG3D71Nl56Z5EZrcNr9zyKqVIWbxvhtutfxTPUq0iTmAcan+FM5wHM6l4+/fIf557ZcQDqjU1uePQuxnbWWe+dYGfRY7R0Cc+JT2J2/pxMZcRj+xDtW9h35yWcvf5dXHHFJ4lOZpy0XsOHeSYvPf1F5rwdnnHnhzG+N2a7XeGe9i6urJ3m+EIBx+sRmiZnmeEXugH3+iXM2CKVfQr6S1F8mnlPcM4tEbbL1MbbnOtPcSNLXB5sY10u8cZ+Hs2scM/OJqWNj3Ki3qeS1qlOpjz48qPEI+fRV/cyN7ZMxwzxwwnmug+hCUVj7jCWqSgQMZmusq5NU/P+nFbkcc2tgvJDH0fVbLrjLm/6N3DL6Sp3bD+Dn1q9jf4tKcszDn67zOaZMebN45ye6zBT13ns/AiMg7Nzlmdf/gYefOQn+aT3fdzobHLp2PeyvPIOHvvcS7l67Ty89C1U7Rp21kAj44yXr6RyzQ/Bnf8TPvP/wt7nDRv2vg4Mj9QQF3FhgsWUuchOWiO1TA6urIJus11oUsDn0eIBVDPGSRcAqJnjPFIFU4W0+yvsbeUzJM9nFrOyzczKOdI9Me3OKDXVodB1mDYmSJXi9imNA/5pssDAaxSZivp4Uwbn2I+TnORoFLMdTbJT3KTaM7GKCXHYRSjFWKnDlOPTcCo0qaD1p6mbl3DJsy7hkdojHLrpEK94xSs4dOgQhmHw8z//y/zID/9bDhyIWFr+Re6977Vsb38WVxP8zJ69mL2IwHaxI4+dXgGEQrO7iMTCjSKapTLNsEhRSUrpNphPpOktmVUc2UII54mDmShSrXtRQa6IXImuKsiSArbRAsB38qU3M+6hMg3TCDAyG89sUiDfVu508ez8Uq0GuRzsmxahZWE2c7Ja1nuowdXseD6RMcq6zMn9SLyNVAZdLaao5/7m0BQIYDxq08cGS+EGHr6j0FKTPi5RZzP/ju0aQRrQj/sUCgWiKCKO47/PU2+IIYb4R0TvtttZ+ZmfZmN+D/GlTd5u/me+uPpKwqzOeeu93PywxWWVdd4w/xBaqFj84hG2rv9lnqO+h3XvcT62/CeYZoWX7Hkzf/my7+OhqTo/euqL/MyH38YP/dXvceT4vbjdJo7vcUX3GK9f/Ss+1l7nCxtTJFKSsIGRrCLCa9hzx78i6dS48fAneVX902SGzq8++02EmuBld3we2QUtkNy/M0vFiqgZYO1skBkmmdCw4hJvrLyP25bP8WvdzzO1OoOaqLFr9D52T93D3NkVMKBTMEmQRC/X2Ln659BKe/Dv/2PC1T9mobCFq/mMH34///t5N/HLk7/Crxtv4feU5M5zV/AoTRbMbZbkKGfiCoah08mK3B7O8ZLsUwDsPjXHNY+NEm3VeKc2xidtnSNJwERT4zP7e7xwa4EjV62wPOPQaY5w+sN7OLd6DWfvPEwGtHd3SFODrtSZi2Ousjvc3tihJWr88L5nsH//z3HdtR9gdNNDAenRVyCEYMSuUsRjMRgQZN2C5/4irD00VJG/TgwJ8hAXsbKeB1iUi10eDK4G4OCp81CZozjRxiThWHE/+kbAqNfB1UqYmsOjYw57OcNnM4PpzkF2rCaeFMzhMdY/gVHzWe0XcPsGO+YYR4XJuspYGC2xzzhFpztKM3WZFk12pkt0tSJptMyeOGYz28tOsUU1cEnDAiE+RqyYtVZxRUwvKwICLZzgwKGDqFnFqeopnvPM53DNNdeQpin1eh1N0yiVjnDdte/n6JG3EIabPPTwG7nzrheybn8EOwgIrJzgWh0HqTJ0u0VEkVIU0SxV2AjGqCpBIdkEIWhTZTRqsWEWcGUbhIUaHMtI11Bhj5EoY8cUFGWGIqOcCbK0iC3WyBD4dh48YkYdslTHMAOszKJhbWKr/PPYfZ+em5Pdqp/bUnwjJ8hCCdLQxTJ8MPLLWQ9iMq1GY0CQR+N1NFXE1z1cPSfYoZG/z1iY+7wTXafQ9/BMkKlNgE3Wyy0WI3but24EDQqFXCUfqshDDPHtgf5997H8kz9JZ2KcI1c/zAu1+3jr2jMJ0ptp6Heze6XNLbvO8PKxUwQNnfXl70be8BvU0jnu2vwwx5MHecXMm7ikdC1/eKjE6bLOWx4M+WcnxpAri4zbM1w58yNc7l7NvZe8jHdNv5Y7Dz0Lr1Bip2Zwx6E53l28jB/uBbxn/V68dA9X3PVv2f/QPP987C+5ee5+No0an951HUaSUPisRmtqln4k+UD3Oi6rLZL4bbQkgSzljAzZiX+K250fQomUZum/8ukf7XO3rrNx6gCf1F8DgD0T0FQ24ztVCs2j3OO9l1Pf/RBjP3Wa+Vdu0X/OPn7q6p9nyXAY2XwnUmlMh2/mrnCdvypv8FPPuoI7briKecdDjwOshdP0exl/cfYyRByh7BJlw8dKBUcfm+QVt83wH87WmG8eQlcRe9I1Okeg3Iz4tY6P1u9Q8FqE+izdRLKdC/BsKYMDmaC79uccs16JLQW31PPG60JhP9PdIu2yzo7/CAA1q4at2iwG0RNf8qXfDVYFjr3/H/Tc+qeOIUEe4iLOrazRtSrIespjyVEA9p94lKQ0xlgx974+WtjHXK/PeEtQNScIJZwZqbEvOc0GOrXeLEtWgk7KfD8l3Z2HXpwNJLJhsWZNcQiN1QGZ21s6Rbs3wSoVZsaWOKfvQWQetdDDVoo1MU1spIwqk976pQR6QqIsCjL3xMZJTjC11OWyK2ZZ7CxiSpPJQj5lYmdnh3q9fvFvFEIyNfU9POOmz3HJ0f+OZU2wHLwTIwkJ7NwXPOppiEyh2236WYVyEtAsV+j4o4zIFCPL990WNcbiBg3TwpFtEIqMnHhGuo7sQSWK6JgSzXSI9YCSkqikiKO28E0Tf0B8zahLmpoYRoidmmxrTSzloJET3q6bu6HcwEZTSZ6mZ9tkhkYaFDAtDzVI09OihEwr09AGBDnYQlDGN3rYev4zf0CURwYEOcXA9ft0dYnMTGJhoPq5reICQW4GzSFBHmKIbyP4Dz7I4hvfRLdaYf+1J/ALNn+wOcvZ2otJREBl5x5eu+sEV7lrNBZmaOi/jtz1g2z5y3xy44+plaZ4UeV70aXOff6XeNe8jr7U5T9uNfjA1kdIpUWpfCPj+FxbvIEbe/vYtsY4LOt86DU/wKG1Jp5pctPq5zmQPM7vTezj1Vmb31IFVtd/gb3vfR7/ZfN3OVBc5A8u/252LtEp3Cr56PiLwZFs7kQcn2kjVIry1lBSclzM8uN7f4VfGruV189M8brpSd6Wpfz5rjXOzykunwgg06jOeqy3J3FY5oH671B65UexDvbR2zAytc0n5m4AlaLh8t2PPI+CH3B6MiYt/ihfvOo1HDl9J6+65zNoShF6XcaDDV62+Sl8WcSOO2SWQye2OVRfY2JC4KcGCz2NQ2qcPWsF9t20jAA+vqVxRUmjOjHJSBCxPTLGhBcy7SaAYis12JvGJGmP+7mKZ9VKuNqAurWX0bfP0RirsL39aQCqdhU93WbJfxJB1i3Y91w4f9s/9Cn2TxpDgjzERWyvr4OukK5iUeym0veodpqkps2Y3iYSOmf1WepGEz0IqFrjHC8JEqkxG5yg1p/EyCzWsBiXPaY2WnQPWCgl2JE+yZaDVZrHRXCmoBAqYy+P0+mOovwEbazNEvPo0Xn2DpbwF2ROgHdbPv7KNJGh0dEq1EVO3rJYA6WQic3EfJWF7gLz5XmkkCRJQqvV+jKCfAFSGkxOvpJrrv4Lbr75LqRdJLLyfZU9CxLQLA8/q1DJPFqlMkngUjUiZJL7fbe0KmNRk45pIEWGkD5K5kQ2NDS0LpRjHwDfqRFrPm4qIXMw4gae6eA7eZqeGXVIYxshFBX0i3HTVQQqUbQKeZypikcGaXoGgW2hdIHyHQzLQ5na4DWKTCvTHBTRSX+bVCsRGD2sQSxqKHOtuzYgyJmycX2PnmYhsvw4JKEPSg0V5CGG+DZEcPIUi298E61yBfPZbYQLf5BW+OBlo8y3L8MNb+VfzN7NvLPN2rmX0hn7HyTWYe7d/gQP9T7Mi8Zew/4kT3n7m3CDn7jqBhSCvY9vcEmwSDHe4WzperraKda7/5WG/dMc0H6f39b/iJ9PPs8nPvlu9m02aOw7wrGDV7LHO8lPLb+b52Yef6Mpvk8G/IeJ1/PIuV/jN+98J1Ya8/Y934X0BQfuXmLp5qsgsihNlynu7uJ0GggEEp2XGDY/ao3wpp2X8nMrr+Q3V25kNCnRcE9SOnsDvfXDOOMx5zF4+HKLwrUP4XQU193T5tedXyRB56bsdp6//SVCo8ifPcug0L6VfmGe47sP88IvHuM5xx6gnCZ8cd9lpHM3A+BJhxMjL0cFMcq0UQiqZ/ejd44Szu3jnuq16OkU17YN1GxKdUnxCbvE66setckZjCAg0zTMtkVRB+HEtFKLQhTSK7+G5QheNFp+4ks89XEAot3X0enmCvKINYKKt2kmKUGaPfHamWuhtQi9rX+YE+zbAEOCPASQxwenQZ8plTfl7Rhj7G+uALAhNIpawCl3N7EvMM3zoPIEvWNOPqFC+Y+zv30AgGVlMiG7jG2tEs2D3y9TdBoUtlzqRq7sPlKLmfLWsbKAXnuE0UYDb8JkOdtD2T/J/sEEi+N2DxTsLffIlvMn4pZZpUzIjizRz1xslZDpKbqpsdhZZL40n7+u1UIpxcjIyNf82y27jmaPkhg5wSwFBbJUIWSGr1mMpC2a5SrCl5SNHrrfAWBdr1JK+yQDNVaXXZRmgVKEuobsCEpJTiQ9q4ySPnY2ILFBiGfZZFpKbDjYQYMszEcQ1YTGjrgQNx2SpBrNYu5HTuLRnCBbJqFjoTSF8kw0qwdWfjlnEWSyQltKFDDjt8m0XEEWg0bCWORNgqUkXxlIcXB9j0TqZCInyAEmBG1qdh6+MiTIQwzx7YG002HpJ3+Sjm7wqdddzaXaWX5pdoa/2RVw5fotuHKT7xv7IwqGyfL6r5FO/Wsa0TafXnsbU84ZXlD8Ph47/hGWnBFWyfhdU5LNuqAUjWeMcGVyO4aV8Rt7f5vv2vNWLrlmicr8IvsO3MORffeztucLtKc/TXBpxk9rf8zvWH/C9BGIVZfDq+/iT5sf5PXNY9ydRfzY2Dy/dfRnee7aKT6p38zOLocf/uT7eKx2GZHrsH37OIcmNpG9mCKbgEL3Jtg3dYYr5x/h2s4zsL3n8byV53PzygtpiABt7Vo0I8R6aYvj5XmqZy12zkVcfdmv81jpapaSEt/V/TB//tgv8j1rH6EceIxwJQC7V9vsPX0r6cgMtcRkozbD/cUAS3MxUFzd/Dj71DRKSlLb5a7D05zY7YDhEiudjhVz9JIeWpLx/oWXc2jlFiypcKsOmZfX/aib37O0sYBObCEVLMjnA/DCeuWJL/LMZ6E6jzF9A573OGnqU7WrxNE6AFtx8sRrp/PPz/rD38xT69sKwykWQwCwuZk3ZE1rJ4kwCR2XgyeWQWisa11uFH1uL14DrQgnzkMlauYEp0opZdXm0bjHke4+Ai2gJRWT9BlpnKc5GdL0xhhNtvGlyy5RxFcZD4+b7ElPEXWKRH2dWW+H/rTBUraHQnQbR+KYblJgqbpJ2dMpTwZst3JiGjs2NRWx4kyy49UwUx1RUKRZylJ3iefMPgcYTOWAv1VB/krIUg0GpLEYmkQxmEBkaEwkW3QKV0CYUTb7GL2cVK4aNfDB0TwyZWNrbZAO0M09yE1Jyck/s2eVULKFriSQkgQK37TIZEJklLGiFqmfF76yFOwM4qanVUQDg9CQpCIjCStUaLNlTOeWEJEhPIk200XXQKEIMg2llcmEoK9pTIc+sVEm0HtkcgwISQZ/q5XkBTRSLm6Qk95Qz8m4hwv9HUbKeYjJkCAPMcS3B9bf8l+Ilpf51Z/6Bd659TP85IE5bot95ju7OLJ1hNdUfwYlL2c9/PdkVZdHdz5LJ/4CL568kfPB1fxC+xTxZW/gv1PgA/4jjNw0zmXtL/HjW+9kTD/HqRtqlCZ9HtCLX7bfJJNogJAa7AFuSGhQRqSCvb3HuHQ+4ZGTs9y7nPCGsc/zM7LPn/pv4J32c7lv+jIMEfNHU6/kZxfezf/5bz9L8/IaG77kg8ZrmXBOEmwmMC5Y3TnIR9ovo1AI2bXP4prmNG9oTmGrnPJEjYO8oyv5aOEo57W9mLtDhHcbSitw3eq72HQ7zBV0bt2Y55/LdeT8i3jPLpPvOdHnS+eX+bPJV3JJus5PC4fa5lk26xMcKl/Hw80v8CzzMHrnYxyrvwR/dj+ZYfDMu+6lGsBtk4Lk8v0U59pMLQd8JroWYg34CJYZEHr5/aLfriHZRqsFBBs2uHCunXB50WFysNJJlsHiF+HQyymWDgMZ/f5ZalaNMMyFrq0wZs7OVw2p5wIWjbPA87+p59e3C4YEeQgA1tfzJ86R4g7HwyNgCw6cXUaUp5HjLSqZx6PF/bgrAfVuH0NaFIwqJ2sJ8+ocj6ca1/dnWLP6SGExEwpcVum5EesNg4Kvs2KNczMam5lio1rmWcl52uvjNDOHK2mRjoesyXEmk0UOxAmbahfbxS1GmybmgS5J5GGRUJoMGNVCFvUS29QoJSWKdYs1b404i9lVzmNEG42Bh/bvUJABtHINI+4S6wUKAfhpTpAzK2Xcz5vV+rqBbmdoXoSeJqxYubJaokemSriyhRQlYJNA16GlUZrKP4NnFBEEyEwDFRP6NtKwUCIhNMvYUZukl3/uqoTjMlfmJ1XMknRACEKZEAYlyrRZNPYQWhaSDL0D0vJwVEIfgYcFmAg0OppkLA6IjDK6FtPUygg2yVRMrLtYSYCuEgJRxPVz0hsYFibg4YC3hTOyF1uzaQZNTNNE13X6/f7fx2k3xBBD/APDf+ghOu99L+95wct58/i9/KxV5q5YcKC5n9ffM83h6feg6TfRTN5EW21x18pfcVn1BJdUf4LfZZT3uSm6c5D/HnWJbJ9LL30712o7RMWYpCZZUxZ2Z4ZzjWdwPtvLWiRZ1Uo0kiorfsLzGpIjTY/nPPhficd7nLnpUiaLC0TVJr35DhO7NxhPNji9WmC76fDD3vv5seiv+Mv41/h9w+ILE9fwg84nyAJJfI/O7t4G/+bkX/L45DRhY5H7JmaoZpJfeHiUed9GItgy4VOTCWvWH9LbNcpneAMb9ncxGm/w3LO3cdee61DCprL127DqUmcE/YYtzOIPsuTeyHt2mdzw2DKfXxLEVKgLj8fSCd4m30q1/RJa5TGqq49z+dYmI4feRWn3wNqg6Yxs3ssuzyT1NhETNabqJwDYbCg03Wc5nsXzC9TCk0QaGFFENy5TAbRKRHyuADVoNFa4ee6aJ77IrePgN2H3M3GcfNXU95ep2lVkmlv0NqInTRsqTYJRgJ0z/xCn2bcFhgR5CADOra7h6xZmJeLh8HKw4cDx4yTlScarywAcK+xjVy9goiWoGmPEAs5XytwSL9BIbYpBnUeKPcZEj8ltj94BE4hYSjLmGxbt0iR7kdynKZQUzBkLNPuTLGkjvLq2zLo2RqpCoqTDXBRxn5ql55xh32adqDdFIALMCHZbqxRlTFcVSTBIozGmd1VZ7OQD0ufLebHY2dnBtm1c1/07/35Zq+N0VgjNEm6Q0ozJC5TdodrPfcQ9Q0OzU/A0CqHH6sCbW6ZHSpWSbKIzghJnCUwd2hplmSvzHdNEUzECgQkEgYsq2AgBkVWi5K2SdHP7SUlmtEQ+omdUZrT1AihFpGf0ozJlFvF0l8C0EalC62QgFKOJxyImTbtM0ffRhENbl4yEIame+9Y2dQcpM9IsIjJKJFFCLevhySJ20AKgb1qYaqAge1sIIajZNZoDv/JwFvK3L4QQ/xb4UUABjwA/rJQK/nE/1RB/nzj2X/4rYbnCzKvewF+f+xfcZZlcvnUp/+Y9Z+nu2cesvkY7+bcseSe5t3kbr5laoy9/hX8NPCYUl7Uf41XWrYxf53B+4gGUBD8RbPV2car3Qu5zXsA9IyapzBuWrVRhp4qeLkil4FPArXGR42Ov4cpzJ8jO30DYn0GhEMUl6hN/jTdjMjHyGOm8z30IbF/j2sb/5A+zEd5y/vv40N6beeOxj/A7z/1pJlyTZ3Q32RebWNU9GFGbu4zTlPtnqRoPcIptfmD8tczOdjnjvgnfKDLTCvkfj/bx1W2snX8OWzKkshNw3cO7MROFecgHtpATFX7lqER/vM1DS3BASW7UTxBJg3fHhzA3D3Dj5n388p//CUWvRxEIHzH5aP01UIKCv81It0tszaFvNdCyMuMz52k2pzmmrePILhmSExuX8qxsgViv4vR9urJALcmQxYTYHzSPh9s8s/YkRf78Hfm/u56BM7gX+cEiNXsOOUhG3YyeZLEQAup7BwryEE8HQ4I8BAArq2v4ehlRzzjb3YeRJEyvLRAf2MuEkT+NHnf2cplcwPAjqsUJzhYlidSoBI+zu70LgWRFmYzLberb23SvsNDosS199q4WKbrz6AjOObmXeJ4FlnrX000t6hNr3Ms16NEi00mKpRQrog6cYQxJd/UAgb5KFtmM6rmie2GChUhK7Ds0wb3dWwEuKsgXJliIpxGvqddHcdaPEZtlCkHAmUQyB+h2B7ufP4V3bR3NVJibgkrUuRg3XVY9Otk4ZdlAk7MkQKRLRFdiW9tYqaJhSibJVQU3EwSxTWbmVobQctETn9ibRimBq6d0VUYmI+oS2maRYt8j0MEbKMixZtJ1C4hIoXdiEmAs67DIKC2rQMXrkIkiTU0wQUSm5QR5W1oYMiPNEmKzSBq2qWY9OhQZTfIHDM/VqfYYxE0/MeptJxim6X07QwgxA7wZOKqU8oUQfwW8HvjTf9QPNsTfG3YefIjCvfew9ezX037wf3PHuODSnaO8+S/PUPQCxPgC7fQnaEXLPNJa4fWTNQLtX/JLWYcTIuOlG5/mRQe/SPn6Fn4CM2s+G94c/+zg7+MWEvo1k6lexI3HTvPM7VXi5ds5YsTc4F5LZD2Xk2ZMu/LXfH5sio9d9iw+dcPNXNI+w5vO/CVjK1UW/avYPvOTxA99mLOOS3v/BNcGt1Hb2yeabJFpbX505jfoHy3TvD/jJ3p/TanygxjWNWxkipL/IEc2HuDe6XkezO6kL87w6ckbSHbP8IhbRnQiilvbXN8r8Mwdwf+ov4ii9lle+PnjGLFHNrhXXCpfTJv/w88esok3+hhnPPZHS/y4YfKw4fPCcA9/oxTXrm5xy9l7OLbnAMu7L0OdvoNLlzeIEx+UmU+4yExW6w7zyzAz5WG6Eevn93OvmeKYDQhhqbUL6dyDEjUKoU+v6GIkCtNJaSf5fWI62uaGyhNhVCzcDuVZqO7CEAJdr+L7S9TKlyPTLgLFZvQV8+rLM9Be+Yc63f7JY0iQhyDLMnqNHSqOh5CwoU0x19pCKkVb6uzSPZbNCTqRjTRXIQupmuM84kRAAS9cZF/7GQCsa4rd0mOksUR3l0IELo7TJtmpUy/mgx2PF33cuE9dbHOyX6Hc7tA/5LCU7kWLly5OsFgSuXdqzunjrdZBrNHUR9iv5x5oksHc39Rlem+dxROLOLrDmDMG5BaL+fn5p3UM9LE6dtgnNEco+A02YoFSoFkdSt3883xZ3HTc5oy7G4CRuM0puYeKWEPIUn5MpUT0QBWa1CJFwxTM5bZfKiTsJA6ZkRP80HKRKoV+gTTVcfSUKIbU7FDNJB2rwGinTWAK4kCnGnXBgla5gowERisnyBNZGxilZxSY7nXZskvsSA2XgEzkykNTGEzKhACDyCihAqhlfZqUmSP3vwVFgehqeMIl6W6ik4eFXEjTc113SJC/faEDjhAiBlxg9R/58wzx94iH/ucfMGE4GKNzvH3sfcx40zzvs5Jyr8cXrnoml2fXI5A8vrHMy6plQv0W3hGd5kvmBM/ZuoNLLz9P+YomI5slDpxZ4Vcm/gPv3p/3fBzagTcteWw98ocUa/tYKy6hewHL+3Vu1eDxqMsvRhaHt17HkS99hh8+8Wb+xw/+S7546ZX81DU/wVX7T/Brp97KofYqx9xncc9GTPXBc9y39/XMfvQz9MtF5q+OuMp9mGK5QfcWDV97jG1+DhT0fZdzQYFKkDAXtPikfBFvmfghtt0ac/4aeH265Ul65VEWVyI60Tqlc5+msLNApzzNu175L7jh8QUOPfhRtjci7mo/i6l7zrKSlpiJ1rll/dOcOnA141mR96sP8qZTE9xy9h7uPljgF9/8q/zqHX+DvTUGyxuMb23ilSZIjSK9xGRlNmT+Iagc6SIjaOzMko1uYOsNJBnr/QnERH6fcaKIdWMMLVU4dkZDSXyhcwiP4mBMJ0rBwhdh3y25MgzY1gRhuEHVqiJIKUrF1pMVZIDyNCx96R/sfPunjiFBHiL36mYpc+oYCujaVW5cfQCAJSKOyID7i0dR7QQ9eyJB72QhwlIBZ+Jt9nm7aZodAmkwlsZU2+foTcQ0/SLjSYuWVmMvJh2VcmbMYD5aIAlc0kgw3d4iGNNYTA5QCu7iSJwrzCdsH5nCTDmgdyr3vG44Y9SzNoHUUbGGoRIUgkLZ5nznPLvKuxBCEMcx7Xb7aTXoARhT49hBQGgVGGn0aIUWqBjd7lDycyLeLD0RN12Km/iVI/SxGYubnDL387z4MYR4ws6RhRKKLUYGaXpOmhABVZWyltg4el4QAytXCPReSprqmEZEHEJidiiFFigotzr07SpJC6qhDxa0iyUUYDZ9fGBCtgDwdItKd501t8qmlJjCwxjE7LU02KNFtHCIDBvVTqlmfU4yiWt66HGI7ypEZtAWRYL2BkVyBflMK/euFQoFtraGo4K+3aCUWhFC/DawCPjAJ5VSn/xm7Ot7/8+dT/nZd10+xQ/ctBs/SvmhP3nqTfy118zyumvnaHgRP/6O+56y/ftv3MUrrphmteXzb9/94FO2v/FZe3nB0Qke3+rxi+9/5Cnbf/KWA9x8YJRjq21+/cOPPWX7z77kENfsGuG+hQZv+fjJp2z/lVcc5ZLpCref3ub3Pnv6Kdv/03dfxr6xIp9+bIM/vO2py9z//XuvZLrq8OGHVnnHXQtP2f77338NIwWT99y7xHvvW37K9j/94etxTI2333mejzy89pTtf/Cag0x+8XbefeMP8R4jJlp4I+f6U3xocpW/nr6J1/oPM188wv/unuXY+BzvsCv0ksc5a4ziJH0qBwUHLj/Bhx56JY+2LmHBniFq6Og725SE4veaGq1wjXeUL6FNlTQaJZq8FqebUuoHPDCq+KmpHqMtF7nnRtTs5Wxvhsx+5Bjh5DQP3niIV13333Dv32Yqa1A+sEan7SA8jeWJN3D99vtYvwP++aG3YKiMSqdNzWsjyhnX1B/jtbMfxbfb/PrqvyFSJiJL2Hv2ESp6lfPzeyiOuzzr0T4nNndYDnd4YxqjzKsID16L5q6zMTaD34YPTn8PHxAJ8a1TbJljSJGxt/s42uQEDQG3hYfp9gss1WPe+/yfYWO0D5sh64lGqTrPTz/7OSSaRicZRTIPkwd4tn2cGyzF1qTDX37pB9gMpuiv7wbyRNNFfwxVyNi2Rvmb8rPwlM3nH5kkFgJ/0uWKtME+ek+ce7EPjR8DuR/+z538yiuOYlrj3Luo85E71ulvvQk2tvmk3mbh88tPnHv9g/xh6yfgD+4A8cQQs2/2uffuH7sJgLfe+jifOb75ZdtsQ+PPfuR6AH73M6e548z2l22vuSZ/8AO59/q3Pn6C+xeaX7Z9qmLzO6+/6in7/PvAcMzbEBcjpsedZbbSMTJDZ//iKsIdxa81qactjhX3Y+6EVL0WEknFGOVkTWdWLdJMwfEnWTdCTBJmuhGa9LAKHuuhScnX2bTrHECjlWYsjVWZ0xfwelV6qcl01ESN+ayIWczkPEfjlE5WZNndouIZuNUY1e0gMkVgO1RUyKI9RVsVcbIMZefS7JNHvF1o0Hu6BFmfmhgQZBczCei3jTxu2uqiJTpmktIqlemGDiWl5XHThqQjKoxFTZbMGq5sIeST/M6JIjE6jISKHUtQlDkhripI0wLGIG46sHOCbEQeWaZhGAEis4jNNkUxiJtutfEsCQqqYf4+nu0SGwZWI394GNPz90NISr0esT7ChtQQQC3J1eGOllAYEPPQ1BBxzEjq0VBlTCvGCTx8B2Rm0KVI3MmJ8Ig9QjNoopS6aLFQ6kJu4BDfDhBC1IBXkc8XmAYKQojv/1te9yYhxL1CiHuHD0r/dHD6t/4MpVIe2mUSahEqrjLea5MJQc8xuLx2JWR99PYayi7RilbYVHl8c0mE7LrmcU4kl/F57fmcdndBJtFShRIw1fexMTnZ/BLoBc6XXCKpo0wTzzRpuPlq2Q99/PeonLuNpLeO0G3qqoKQOlPL9/Hb7/5jrtzoEeuSpWqNk9YhkqqBUikyOEXRmsFBZ3Z9EaMXslyZope5xDsmby9+Lz9e/F/8dvrL7IRTpKGNkoDMmA03uH7xPL/5wY/hbryFQm+VYhhhaC5mYQpl1Xhp9xC/+ZBPVdRRZGSpomnWUEIwozawCzH98hhFKTFSKPdjYt1kqThGJjTMJGbLsunVKiSahhnHCMVFy0YhjgivskFXmHGGBKTSyESKRNFPLRJTYpkaYpDHqpRADhhaiGQq7T7xZYaD/7aemIlsmWPESQtd5LqnJCP5yhrtDhrW04gh/m4MFeQhWFlfJ1MCt+RxZ3AjFGH/6bOk1VlG6i00FI8W9zN3LmB6R1AyRkDqnK6aXJ3cRxwVsZIiG05KXXrUd7p0D9gIEbMYwe6WiVceYx7Jo0DftplT52mF46yLMpc5j5JaKRtZhdFkgz1hwrraTcvdZrRpYOxOyOIehTjGnQypi4jH7HG2gxGsxMao6sRZzEpvhRfvfjHw9U2wADBnJrDCkNDKGyKsjolUXXS7RaJ2UQpDmuUKG9ujVIBCOoibFlXGogYbZnEQN+2gAAEkUiNLOoxEGafKOkWZ0gAq6kLc9AapEAROToLNqEuWaZhmgJWVaNlbjKoDQEah5+FN5tWy5udF70LcdLEXoVKNstFFSRAZWF5AZI6yM4ibHom22c4sejKkqOcNgIGRqxcTYYtu0UXqCa7v4dllZGbh4aB6uWo8Yo8QpiH9pE+hUCBJEqIowhqo30N8W+AFwDml1BaAEOL9wDOAdzz5RUqptwJvBbj22mu/oaekC4rS3wbH1L7m9pGC+TW3T1edr7l931jxa26/ZLryNbdfs2vka26/+cAoNx8Y/arbX3B0ghccnfiq219xxTSvuGL6q25/3bVzvO7aua+6/Qdu2s0P3LT7y34WbXqcfdWv8+DVNxCNfoyCs8HUI2/gtz/7Nj5/1aVITzI5/69INm/jeycuY3r57QRZh7fO/Qj7e9v0v6vCx+R38ah2BdMHNviPZ+7hndZezk3O4ZcK/NznT9HKdlj3z/LPNh/kde4YJy697OL+VaY4mYIuA56/8XEuvd8jnjxM7cofoWDuITxxN/H5W7n6C5/mS5dfz1ve8CPslMt02xaXH7+T6x66m1MzeymHLv9i/W62ZQshy2zpe/iBe97PB8Mf5MQl13O6YbNwuMhYOeL/K/4k3tYYrz39AJ9tX8nCqs7lHYcjxic5O7vG6/kNdmUGVi8fjynWE8qViF2rH0AAb5v/Qd545P3IT7RID8zQV0WOje/nLZ/+Y4Lm4/zNs7+PE2KOXbV72HH2sl4uMxZ3efMD72XP8iqfev4P0B6NKZy9h0tmPPxrFHNyg9+P/yt/ZvwoZ9w2C+VTtJd+iAYOgW6wWza4autTPLD/EM898G7S0YhH/+wAe6rnqMR7nzj3/uan4aF3wU8swqDGn/HHOVj5EG965Y1c9843Y+/+z9j2NO++7vAT597hUV5w75vg5R+F3U89h78Z596T8aZn7+NNz973Vbe/+fkHePPzD3zV7T/3ksNfdds3A0MFeQjOrazRs6qI0YwTSX4C7nv8GEmhyqSdK4/HnH1MqDZWP6FmTbDqCPqGRSU8x5FO3hS3rkzqok+t2aC7PydO64TYqyUK5jQ6giXziQa9nl9nQ1SYH1lig0mUaqKymJk4YkPN0nU8KqFF1J8kJERPYJe1zogW0BYFehQhrjEyVWC1t0qq0i+bYAFfh4I8WcOK04tqbs3TEWkeN+1fiJsuVWj7dUZEhpnly0BtUWM0btGwbBzZRgjJBcYQ6hrSi6lECQ1T4BgmsRZQyiQqKVHINvENi76TP6eacYcsMTGMACu1aOgNbOUgAMsP6Q5iqcvBIC7atPK4aV0nDYpYpgd6fkkbQfzlcdPROhpl+maPwdsQDsZjjkb5klWiaxR8j54JMrUIsJGDEXdPDgu5MBVkOOrt2w6LwI1CCFfkna3PB47/I3+mIf4ecP4v7qbvr/PAoXGWC8skvWt444MfYHFmhjjpc315L6Dz4Ow+7tr8MHHWIZjdS69c4twLjnLW2s0Cu/l3p/+CL37p+7n2DHi2ze71JWbbPpcEE0SL9wAQOzVOXHoZemubyZ3jbMWCRVHmoL7N4vXPY+2ll2AqRTS1wOeOvIPHC9vYV34/j776V/mDZz2HgrfD29/yG7zm85+gUa1xeu9VbI/Osmv1HMf3XssvvfGneM/Lf5Dtsslo9BCfO7yb2ZXPc9nZJq9v6tz4SJt/+QlFvD6DYzd4x/mreGC1hFcyuGR5i6PcxI8Y/46DGBgK/vMRi/95+D/x0VqP6zoGrV05Afwu936umP4SVkGjr09hNjaYPX+MdOs4d9/yeu45kr+uFMxQ8Vqsj4yhBPgiRQDlboNMKJQQIHoEhzwmdgLO9erYaYyTOPhahCZSQnTaQRlbTxBZ3sydRXmB1p2EfqYj+40nvtCV+2D6qovkGHIFWamEJGlRsSroWZ9mnH75iVAekN/uU20QQzwVQ4I8BFtra2iESFexxDxVr0ep7xHoJnW9Q0crsKJGMc11SAOq5gQnizkNDKPzzHTzJ8JNCSOyT7W1TrQb4thE2F3CbYcKeYPemUI+Mm2ORXq9GkmocCcjlplDj5YHEywy1skJ2Sga/c09RFpGhM2EuYEU4KcOAEk8xt4DYyx0ct/UkydYFAoFbNt+WsdAK5hoZpHAyotS1dMRKWh2j35WoZT5NEtlYr9I1YgQA8vCjqgyGjVpmyaaSFDSRw2KVmRoyK6gEgckUhBb5TxuOtMgs9HjJn3Lxnfzy9CMuqSJiaalFDODba2JRKMIyCilXciXKY2wjKM8fMMktCwyQ5IFLobVQ5n5e4ko/Yq46U0QJXy9hz1IDAy0vBDXB+PdVGbi+n26mo6WGaRCR/j5BJMLcdPNoDkMC/k2hVLqbuC9wP3kI94kA6V4iH+6iLd9tC/ezvGjR1gsLqGE4rmnAuabXfrkdquZ6qX0tSXU+mla0Sa1+Xn+5Io3ED1jnKCk8dr0L/nfC/8v/3r5TxHpQbSFBm/7T7+A5zi86swGQkg+Vz2NbyqOX34EUzaYH7ufQ89b4tW3vJ1HxBhny4JKaYuwsYu7bnwm0bxiz/QDpDf/Att7P8RNzPBju57F6dfM8fuvfjk/1j3Cf/voffQdmz/77jdx59XP45Y7Psxf//t/yS/9+dsZ911aI/voWw6bdR3R/BPi1v/i+tU/x+v+Lt3NFlbFo6tMnjGxyMv2b7B/1yu5auZ6ZqJxInKrw8cmYORheDxbQ1eC5ewFAFwdnkEaGeHcbnQR4myu8oaPvR9Z2028/yrOj+c10QzHMNI2zXKVSqQRaLmtotLOvbZK0xFjPuiKie2Qs70R7MzHzXKri0ZOYrd6k1gyIB2EN6X9weqcG9NLdejnog9JCOuPwMzVX/Y9m1Z+jw2jLSpWBZH1nkqQ3cHKxoX3GuJrYmix+A5HEAQkvse0mTeNNMwxLmnkjetLKGa0gGPFfahuihALgKJqjvFpJ0Aql9VwjaP9V9E2eoRSYywLKXeXaU2ktPplJunQScrMYROQcboGk8E6RpySxBa1VhP/oMFCdBg9XmLfYILFInlxmLV8vPURECs0jSqTxnkA1GCChUyK7D44ycdadwN8WUjI07VXAAgpEE75KXHT0k4IpEs9a7FcnkH5OqWq92Vx0/WgTTAIN9Jll0yz0FIvV5C7grLTA0bo21Uyz8eOXSAjC0L6pk2qBySajR008KMn4qa3ZO4zG8sy0kTQKJpATByPUqZDaOu54q0LlGejF3ooUwMSiDIyWaE5UJAn+9uklTF8cx1Tyx8aIpkT5FrUyo8BDq7fo6dZiCx/UEiTCLLsIkFuBA0OFPIlsCFB/vaDUupXgV/9x/4cQ/z9oXvbCt72I5x55hHOFG9FRFNc//gSUglWqwWmq5NkzLMSPcLp3sPc/czXcuclV5Apxej5DX4suIujh9/DwfsDCvWQRvRCFuQa73rDj9MtznB0YYUdrQ39CH1yAkPZTBz5AkFpm9v7Be5pXUWneD/3VzLS1TX2tbdZnzzCsnwRy3cewzDmGB9Z5LI9f8Z1C9/L6xe+i7Ur/hfnr1xjau163n6syM/t7nLHdbfQqNYx0ndw1arH3uXPI1AkQLNQ4NGJWRr1XdiYnJi6i74qMSl3uPxohyt7k2zE/w/GXBEhBEvdBY4VKrxEVvn+T34AbUWneXSJrL2fA0Zegzttn2TtAF1R45narYTrPnaUwI0vZ7/XZXNkN0U2UUmFFA/Pdhj3TfzBPaTQy1fmpKEjp2OMvqCwlbHZKzCSepiqRkqCKRJQsOWNMqudohflN5PYK2CxgyjGeIEBiQ9RHzaPQxbDzDVf9j2bZj69KYq2KZtldpI2vp4RpBn2QCjJPchiSJCfJoYK8nc4LjToTRmPk6AT2AX2ra0izCIbdofRLG/Qk42QwoXldnOcExXBFCtsJwlWMM6mEaCTMtON0TIPq+yxGViMhJItt8YBJI0sYWW0yLxaIGiXiSPBbG+bpB6ylO6hGJ7l0sEEi5NWgMxguhShdvKcglV7glG1TYZAxAKhMmRqMjJZYqGzQMkoURuk212Ygfz1QBaqMCCNxdAiTgYquS4Zj7dpF0vIIKVq9DB6OUFeMfP92bKPUjqW7ICwB7+nQUNSGjRX9M0ySvgYWV5A0yCjfyFu2ixihS1SPx/HVpGSLdEDYD71CZVBxzVRKJK4Tpk2gWkSODZKU9DT0e0O0hSAIkkEmVamNejymPV7pHoZX+8iZK4AR2Lwtyb5flLl4AQeqdRJByP2+tjgN79MQb5gsRgS5CGG+NZGFqV07z7HmUpKy+4SWDscXrE5vNGg4ZokmuTI6G4g5Uz7PO992fdzx2VXcmhxGevWDQ60JLtHv4i2ZeFsgFKSdnQ1H7jme7lq/RJ+/BMdru7W6Hg2KkyIzF0YUQXvc79O66NvQd3x0xz90nN5YafONRs6sV3D6vV5zue+SKilTIvLOV87w1+7j/Ef7bv517vfwrroM3Pvz3Lu5LN4t3srH77kV3i99t95ee9zHD9wBeem5rjr2qMEr/wNfvO7Z/nQDXUCQ/Lss6d4yNiLWXgxDx88zCPjLQAq8mp24l8mFAlZ1se/+/dZ8XcwyYno/kaX5nPGuW35KGsoDts9HK1IFrmcP3cVRaPNM5sPsmerxdqUSzA9wXSQkugGZQFh6mJjERgWBWUSGLnuWPDy1TfDkYiphPHtAG/Vwk4Feprb0zTAErko1PTrGHpAEAbINCX28wY8UUjoJwM/nN/I7RXwFIJsGFUA4rhJxaqQJjlBbyZPGvUmNXBqF+fbD/G1MVSQv8NxgSBXCk1OhQcHEdOLqMochbEutoo4VtjP9HrE9E6Ko5UwNZfTNcme5DgrqY0dVdmwWtSFx+h2F2+3hZQ9liPJZMfkTHmE/WgsJYq1epUbOE/Xr9NQLrNqEVltsxpPoyeLHI5T2lmJlfIWZc/ArUV4nRZCKdpuhWrWZ9Wsk8Y6rorJzBQpRT7BojyPEIIwDOn1el83QdbKVYzEI9YcnFAjSARFILVSxoItUk0jkBq6kyG9GD15Im66KDwy8ka9fBbyDpGuoVoapYncO9Yzi0ixiByMXAv7DsK0YBA3bUZtEm9//n1IWJF5EZ1SMY8JGyUFkUyIgxIV2izqo4SWhRAZsivQ7C6myIiBMNFQskgqBJ6UTEU+sVFBGB4hM4BPQkKGxExzopwo92LcdKjnBdmjAN4WtZGBdSXYuWixGHqQhxjiWxvB8QbpyiOc2buXk+4aKMGNx/qU/IgHd8+SOjZjah+N9CR/ce2lLE3t4c0PfJ7blkwK2gRXo+Ne+TjOhzUKe0I+bR3gvl6DS5ZcTozfhe10MNqv4K7iZ8jcEpmhsLJzNPQOFaOKK+vE0Qy7O4dx1SCwSYNHL4XpDZ9u5RFu2ryJskhJPcWqK/mCfowbOMjrVl7H57q7+N2pdxHIbbLovVB4Nh9+8Ty7zn6EU/EWmTHFRrFEceQG+l/4U65urvPQ3CFecOxaamPTMPd20mKFUuud3KO3CZOAhfmTPHSww7Xn7obaj3P8sufyqdDHCRX3FVbYH9t09DJbykMpwWTpMRqfK5MJwbHDE1xhxuzq5RY/04BObDCW5KJH1zQJdY0McPu5iGJPJAgNpnZ8uqsliq6OkeVWQzMzcbQepNAOS+hWQqLJvGFclHN7nZMQxgOC3N+B1fuhOJGHfjwJhpHfi+I49yBH3R2woRWnTD25l9qtQ39IkJ8OhgT5OxwLq2uE0sKoxRcjpveePkZU3s1EMZ9g8GhhP7NBh2Ivo2ZO0TQE206Ba7yzFNuzAGwqi7psMtLcoXPIRtBjIYvYu+5imLO4CNZ0RSYl8+o8zXiCVVnlxsqXSKTGplFkNNnJJ1iwm6a7Rb1pYMwmZFE+wcIYy6irkPPuAZqdCnYqYZC8udhd5PKxy4Gvf4LFBWiVESy/SWyWcMOMbpy/vWb3qPk5GfQMDd1OET2NQuSxNmheKwmPRFUoygY6VRAC3zAGcdN5MfJMl0yFCCXRFQShS1a0QUBoVXD9bZJevkxWkYpHBnHT46TcpeWqbail9INSHjdt2ASWjVAZeidFaAnVNGALSU9aSAW6sOjoGmNRSGRWMPqKDaOEED6KmNgsYsUemkoJVPEiQfYNGwvwcMDbwhk/jKM7NIMmpmliGMZQQR5iiG9x9B/YZDk4S780ypq7jhuMcM1Cg8Aw6BkCa3KSTM3xjsrDHD9wOS94ZJWfbPwWb7X+kCutJofG83nVcnfE71PgVPOlXObNc/LSt3PXdJlXrN8Ibbi0rXNfpY5IE15jfIgPb17K5fuO8sAuh7cns6gVjz2zf4Six499vIaTTfH4visYXSnTHdfoFDxsJtm3vh+B5DEgsVKeq67jpua1PBL2WdY7/FEhwkhfyPMWL0VLbA6lFhKNBwCu/yXKwPNTwaXmIUY6RzgVvZ/z+iZhoGFWV7i3+Cy+uHuTZ98XQ+CT1jLO9GNuiNcYtfpsptAVJmVTIMKA/fu/hDy/QHfZYWl/gUhoNIyMvVkZlEKZgkYkmItywtsxJQhBYBhYSa4Ma7WMxNModlLW1y2KuwRJkr/ezmwMrYckoxsX0eyUWM8JsqcXKCoT6aTE4aCXpj9QkGeuuRgQcgGGXgEGBNmsEEbnAWjEXxEWUhjN32eIvxNDi8V3OJZWVgm0MoxmPK72o6Up82srJKbNpNEmFhpn9FlccxsRh1StCU6W8gtTRQvMd3PFc11CXfaptDYI9kCaagRml2TbpcQkAOetnFDNs4DXq7FDgdnRDdaYRqTroDKmo4jNbJau3aPqm6TRJJEKMaOMGWubUT1k26iyQxWZFCiNWYRpyGpvld3l3cDXP8HiArSRGk6/QWSWKAQhjST/O3W7Q+Vi3LSBNBSGJ6hEXbbsfB9l1aObTVCWDXSR/ywyNERHUjA3kUrRNDU09UTctB87+F8ZN93Nu4yLekaHBEVGXSpaZhGZpgSGwgtzBbmvu/i2jUgUejsvgqNZbpdoOSVKfQ+JS1sTVLOIVMsL6JZmo4sMVERklMhijUrWw6OEEeV2EM/Klx893Itqw4g9cjFNbxg3PcQQ39rI+jH+qSbnXB9P+iT2JlefiRnr+jy2Zw4BXGKO0RcZ77viMia2d/iF1bfy3spN/PgVf8xPPOs3qB/5BABfKEk+aBzi0vVn41e3eN++17JWejVXtEZpyA7NXpe0VMVUIY9k+SShMvu4dXQGuxOjigZXNp/DjQ8pdq88gsgeYnH8XpqFt/PPHvpzjpxbInDXaUzezsQVb2O+9SHStft5PAhIEVznFnmxVeNoK2Sj6jAxcYrxXXcSpXcTW8ewawuMF0/yYrHFs0s60uzzAeM8G0mCXznLQ/7LcLQlLJXyvJWbKScmy9ck/IF5N0fTkxhmxviuB/BGr8IXEe2Si4xjxupn2f8xDaOQsHnIRngpW5oGmIz5XRITekjCdBGAjqawpENomsgsAwWqIOieK7IuXLJYUlACktw2aKYmmu5hkeLFLpqTEmkaVhjSxqErymh2SjKYaEF7GbZPPaVBD0BKA00rEscNKlaFOM5rdSv5yka9+tBi8TQxJMjfwciyjM7ONjV1HqHBmpxmtrWNnqVsCklF63PGnSfqS5SxAKRUzXFOOPnFvRauUO7voq/5eAJGs4Bydxk1FdPplxk3Ynodl3FKpChOVSLsJGA03sL3S9CPMcYSltLd6PES00mKScY6IyBgVGn0t+YItZQIm3lzFVOk9HBJ0cniOjO7ayx3l1GoiyPevlEFWR+t44Q9IrOIG/isxxKlcoJc7ufe6LbroFIoxjqVqMWmm5PhWtrhnNhFWTYuxk0nUiB6AlloXIybNrLc11wREUHsEA78aoHtomUxql8lTTUcLcUHUrNLTQraZoFyt4NvCsLIppy2UULSLpURkcJo5QR+TOXLei27RLXXAVmioUlKhGRa7mnbliaGlgApsVkiDSX1tEuLEjIbxE2XNIQS+bHu5t3YNatGM8h9bcO46SGG+NZGcLJJ1ttieWqc407uh332IylCwXqlSFAscDAZ4S/Gd+gWy7z4wSUmp25n8orHODpyku3zN6NSiXoI/kK6vPTcyzCF4H2XT1JpfxG0Kpd2TVp6iy3RRmk6mdTYCEoILeNvjBX2njmO6voU9YhJL2CyYVD1FKE7gi/7/MUNPX7+1RqVXTdQzGwy4FxrCvuZn2XXw39IM/k4zblP0ht5GFFe4RmeTaRL9kbXcUNykJdO7uZlxl5erPZzk34ppuXQO/Y+/tXcr/A/a3ex7E/hWA2irMx0exZn8SyZYbG95xqK3WuIRUKDXfz1jc/g4PyjbFQmMJWOZpdAZdi36RS2YOyKDpaZogLJ6qDxec5rYCmPFElPz2tkT0sxNYdI1xGARkKSWuycrXDWyEUHK83IBqqulVqg9THJ8BIX6WbEmsQKQvrSoksJ03oSQV4fJEB+hf/4Akxj5KLFQgzEkqdOshhaLJ4uhgT5OxitVguylCmZx6p2rRr7t1ZBM1iSfWp0eLSwH5oRZpjPTawZ45wsZdTVFluRhxVMsGn20UTGbDfESD3MqseW7zAeC7bN3H/cUAnLdZu5eJG06UIC4+0dwjosRkcwoiUODBr0lgYTLKatEG99LA/k0CsUrdzmkCY5qUziUfYdnHhixFvpiRFvpVIJ0zS/ruOhj49hBSGhWcANuuzEOiiBZnUo+nmRaZbKJIFGIdUoJU26TpEQg7GoyUlzdkCQB2l6QqACgXJb1EPFtiWxBzMuqyojSm30C6EdVu5p07rkcdN6TKwgNTuUZX7jqbQ6+CYkmaAa5uS0VSwjI4HRuGDHyG+EHaNAtdslFWW2pYYrfJTIvcNNqWFrCaCIjAIqVNSzHttUcUX++0EBRKbjKZeglfvUR5wvV5CHHuQhhvjWhX+iwVL/BLFtseau4QQWB9d6bI3UEFGf5tgsZId4z95RpjaWea5+jEeOlNjsj/L22/894eLVCC3jtqJkrF+n1L2cXTLk3GQZxRb7uxmOkiT2Cp5rglJ8X/hXaH0fuwJXqiLbdokw0zjSWSYw+jCWK9f9Yondyxo/sRywpsX8zL7f41OTnyE2fKKgyn07r6FRqzEx9WHCPZ9l4dI/YfGG32Bz+X0A3C83ybQAUQzoFk7xUPPzfGz9z3hr+Juo05/gVXfZ2KUHaHozaHZORreTg5wY3U9PmVgCziUjiGyEq6Vi98Y2Dz34Etp6xERWIdVzEmx+2qQ3K1HTKQUtvz9tqlwgmuu3GRsIBiLLVxu7UmFLl3jw+4buEwc2vXWXBamDUcCMU8JEQyiFndoorY9BRj+zEG4KQmAlEbE0yDID08wI0oEbdnsQcT79t0crG0b1YpOevEiQv4rFYnAvGuKrY0iQv4Oxvr4OwLi9SiurkFgm+xaXEeVZknqXWtblWPEA9Z2IiVaEIUyKZo2TIxYz6QIq07GCGhuaxojoM7bTxZ800PWElUij0tNpVGscQKObZCyOjzCvn8fzqniJwUzQhHqP5WyeQnSOy9L8Qj5lh8gMpoox6XaujK45E1RFbp3QolyF1VKXmX1jLHby5a0nh4R8vfYKAH1ibBA37WBHfbq9vCjpdhc7lGhZRrNcoR9alDONYroDlk5HlBmNmyyY9UGa3pPipmNFYnWoRxfipvMiW1OQpAUsc0BIndxjZgT9QZpeCKlJZLYoilx5KLfaeHauatfCgaJdLJEJgdXMPW3jg/hqX7OpddrEeo0tqWGKAG2QYNLSsovFPjIsCBNGlMe2qmAbAUYc4rsKkZm0KRK2c4Jcs2pDi8UQQ/wTgEozgpMNTmsbpCojcpe46bjAjVJO7plDKMUlWoEvjLrslMvceOwc5Ss/isokv/PAv6KeTeOOH0Ol8DeWxWuWrkWgcMUOerxAaI1zZTOv18oLSYoVZNpm2mzgtywqboEZGz6zKydyZ+bnmOgqir38obpXLBLXp3GCm/l3d8/ykhM223aDD81+lI9Nfo6uFvKZF9zC9vlrSWIT3W6SxQJ9I6/1d4lzrO15P49c/of82q738NuXfIDHiueoNcbYKjk874EdDNVh19Z5HCMArclpfZppx8rJ6HLIwe4aBW2d89kizzn9MP3IxRMpdVUikAqFIIl1tl+V0ZE6JZkT44ScFE93GlSTvAa6URE9SejpEkvLCbJCYToeqeeAEsQpCKuEESf0EwNdCczUJNV9dBR+ZpK5OWk1VIqSGlaaYhkZGZJYaNBcgJF9+SSKvwU5Qc4VZFSEIdTfPgtZpTCYfz/EV8eQIH8HY319nUyBW/Z4KLgCgH1nThJVphir5sTt0cI+dnkeIy2omOP4GiwVS4zG59jXmUaisYFFXXrUmk3ah3Kidy5JKG27pM4U40gaaPRclzn9PM1ognVRZspoIt0+K/okIl7iUJjSyYosO9uUPYNCNYJuG6EUK+4E48k2bemix6CrBCXAsg0WugtUrWpeFPj6ZyBfgDE9jh0GBHau5hptC0mGbrVIlUspjGiWKmyFI5SFoJjmxLEzCAtZN0s4WusJBRlIhSTLOtRDxY4pKMm8WFUzgUqK2GySCoF/MW66Q5bpmKaPmdl0rB0K5Me01OniOfklW81rNb5pE5kmRjdGKcGo0by470K3R2TU2dA0BDAS7yCUpKslFAcEOTA1RJoyHrfYooppRji+R98BmZl0KZL2toBcQW4GTZRSFwmyUt9Q0vAQQwzxTUR4vkPmJ2wVdB63ApAxNx7PU902iy6prnMlBh+YTHD7PZ7pniCsBJw8fSnNsMZM36RSf5BmD/REordvZspIOV7RML37SMzdXLMTsaU36bVjMsuhEG7TNizSUKNqjnPeNRDegEQXDEZbPmPLSwB0SyW0XouOLHP//E0UrJfzsqWXcbRxlEhL+OT0Z9hxutw3e5A/PTfH29arvK9h88CBFWTqc+9Rh0+Y56ma22ypiHE5y+4b4eDrzvGlQ9dSiBSvvDtDH8vrYTz5JRYcjVnWeNGjt/Ivvvgh3I5ihlGeF1/CX1z/AlaPPoAmAoqqAAIy06K130YdjmhKjeqAIIusBYDV7YGRK8dWUqXod/FMA1M6hJpAIHCURxbnAkchEijTRY9j/NTAzBRWahPJCI2MQBnEto5AIS9Y8eIYS89JcyB06K5/VXsF5JMsLjTpCaAgFa3kKxTkgS1w2Kj3d2NIkL+DcW5llb4xAqOK4/FRAPYvnCF1S0ybLQBO2Hupag20MKJmjXOmKFFCoIXn2NvJE/Q2hKAu+lTbW/j7NJQSNDQPsVmgKPJRNEvGEw16XX+UDVlmtrZBhMGOYZJmXebDhHVmaBY2qHYNjJIgCzu4YQyuoKZCHrdnCRMDVyXg5IVjobNwMSDE9336/f43pCCbM7nFIrByQlrrasgsj5sOVIVSEtIsV2gGo4yIDEM9ETc9FjXZMR1c2UII42LcdKRr0A8YCRMalsDRDRIZXoybttMvj5u2og5ZmhNkO7XZMbewyQm31Q/oDXKiK7lgjG/kcdNkgjQsUDB7KF1cfH1s1Nm+GDe9hpGV6GkhRf0CQc4/6VTYIsIAA4r9Hj1ToaUWPg5i0NAxYo0QZRFe7OG6LmmaEkXR132chxhiiG8ugpNNOsEK/XKRRasFmeLQasBWfQTZ77IzOo2pTfGlyRJHzjzC+CX3UOwlfHD1hdTThHrSRx/b4H6l8/KNXYRZhRnD4o7pGk7/XpS+n8OdjEVrmc3MByGYDDZZVnmfQ13u4dHSCOV2vgJYT3r4SZdyEJNoOpFpUtk6x5vFn/LqT/w1h7rH0JTGTH+GF6/ewi2rt9AyW7TNNvu6+yiuXcqDgcnyZIgebyHEGMbWJJqAl+88lys3b+CKx/4N1oPfzebcfpYnL+WVdyvOhXlynHI6VNu7uIEHcI0+WpZRjBUxGrvTcXqWyYlkgorqgZ5b0TLLpnOgjC5hR9OoiZwg62mHjugTxClLE3kDukxKFPwOnu0gpU4wcES4YZ8ky8UPJ9ZITRsZhSRKw8xSrNQh1EIkGRE6PVXAMrKLwsNIHKHrgFAEmcjDQr4GQdafZLEAcERC+ylNegPxyB8S5L8LQ4L8HYyN1TWkCpHljAV2U/R9ap02PSEYMXqsWGM0IxdlLYMKqZoTnHDzgrcVL1Hp7yaSES2pGCWg1F0lm0no9cuMOAFew6am8ovxdHHg22IRz6vSzFxmRzdYZQaZrIJSTEUhW2qWjt2l2jdR6RhxFuBEKaNGmzEZsOxO0aCKlRiY1Zz4PZkgf6MTLAC0qoshLUI7L2hVz4BUodndQdx0n1apTNgvUTUjtChX2XdklbG4Qcc00UWMEgGZGMw61jVkT1COA2IpSKwKsd6nkGmgTMy4hTeIm1YIzKhDmljoekwxM9nSmujKxAa0MKZTGAyhDx2kSvHNC3HTOplfwLR6KCPftx4mZLLM9iBFaaq/iqSMb3RxByT6QiEfD/PjlmJQ6HdpGwKZmYSYSD/fNuIM46aHGOKfAsLHWxwT5wHouStccU7HiVPO7N6FGQUop8Tnxg6SaBo3eCfQijvML/ucV5McBpzR0wgJJyKNy3aOIokZ0xV3zhmgWpiiwkwoicweLSMGlbFbrbMW5XM3x7IjfKk2jtWNyRyNyb5HN2lRCAI8t4RQGQUtJMs0rGbAmJGTtdsmb+MvmOBhK+Xah87xrLtPgoKZ7i5esfwiXv3QtUy1dKx0lGcv3ghAVFNYGOzPRnk8GGFEbXLi8Ev53PNfSLmTj/7cG+9g+LsIsiK2m/drWFlGlIKGpOY3WVYTFFQbO8oJpTIsImEjgQ1NMibzWuckPY5piwjg9Exu6yMtYYVdum4BKQ1icxA33fIIsFGAGUliy0LG+b3QUAlWahHJCDGQVLbDOraekQz8wXaqIwRoVkqUDeja3zLB4gJMo0aa9igN0gAtET3VYuFcIMhNhvjaGBLk71AEQUDke0xwDIBtfZx9O2sIBEsioip6PFbYD+0ELV0BBgl6hRhX9dgKmtjBFJtmDykyZnohVtTBqPXZ8V0mM0Ujq7IHgxYpizXJWLiJ1U5IUxOjFyDGUhajQ+jxMhNpik3GOjUQUE81guYsoZYRK4s9xholLaajFWhRRiQl6lMF/MRns7/JfOn/boIFgDQ1pF0mMi+otC4qAWlE+BSopR2a5Rr4OmXjSXHTWo161KJv5peTpvVQ0gCliAwN2YHKwKvmOTVSzce+mKYX4Js2mZYQGy5W2CSLcotHTehsafk+JtIEFQtaxXy5LkvqlOkQWAahbZEZAtV30O0eysrfW4QpmVa+qCDPeRtksoxv9LAHTSSRlhfPkXDQbKLsnCBrJjIz8kbDQUPgxZTCJ4WFDAnyEEN8ayHzE+LVHquiQzcTpPYqNz2WU7CNaj5h50rgE+MG1fY2V80/hAxN5IaNj82ssilVHiZVILrQ7F/HqNwiCxqE8gyJuZvDnbxuWCT4toGhuoybPbbCIkYhRSfmRGmUxE9RBZ2Zbo8g7WFHEb1SGS0KqRgRcVAg1g08s0yGItACsqiK2p6gL7c5eGYBR6VceeXHsWRIPDJBIQnolGo0uyZKCbSST1+EtEWfdU2Rmjo7k4u0SzaX3ZHf3/RBb0aSFnHsnCBLUtJBWmo9aBHro1S2l5ncWEJXEmE4JH0TIWDHlLhphmaluIHHKW2deaXjuw4akKYOZtSh4xYRmo4xm++j3uvlYonU0GOdwDQQkQ9KYWYhZmYQaDFS5MezHVax9YR4oPqmSX4v0K2UOB3MPZ68/Kt+9xfCQgwVoQsdQwW0v9Ji4VTzf4cWi78TQ4L8HYoLCXozxmkyJL5TYt/KCqI0yXahx3ja4NHifpydgEqni0BSMUY5VdOZzRaIM4kV1tnQBDXhM9rsE1UEhhWyFhrU+5KdQYNeO0tYGS2xizxiOosypnvbxCMxi9FBjGiJg3GuTC9fnGAR0VudAAEdvUy9MEh4Sy0UkiQeZc+BJxr0vlJB/kYIMoB0q6RaXoiKgU1yIW7a1BhLdmiWyoggo6J30b18ZvCaWUUnw9BClBKYsovS8sIW6hqqoVFJBnHTVgVkH31AkJMwt0nkcdMl7KBJ2s9vYhUp2B7ETc+mAVGm0yjm9o80GqFMm9Aycv+yBvQMdLuDsPLLOo35coLcb5BqZfpGF23gk44G0dq1OCfIShUo9Hv4uoNS+RSQJMsg9i8qyI2gQbGYK0W9Xu8bOs5DDDHENwfhuTZKKTquzlkrAJlw6UqCV3EJspTQspkzyzxQtzi49BjO5DKVLckH02cilWDa03Drj7EcCW7c3kU/G2FGN1jQQ4zwMVJ9niOdvG5IPyGzXYRqU7f69Dwbu2iC3MDXdIIwQbk6u9t9hFIYSUK7VIIooGb4xJ5JYOo0RZVYJGhKoxRDGtu0iqCniprsUirv8IL6x3CWz1AMPALL4aGawR23vwFO10lEynusOxFOB01kFFp7eKRwH3F7GRIQMq9TWVqm6OT+NC0N0cL876j7XYysxCvf83HS2MNVFpgOmZ/X0n5B5GPb7JSS3yMWKVekLgiBrYl8IlHSpVMsoTQN93B+vyoPmhKlLiHW6NsaoDDSDCML0JEkJGjkhLgTVkgNUGl+P4wHYolwErJEA6mDYX/V7/5C3HSStChbZTTVp/WUJr2hxeLpYkiQv0NxgSBXC03Ox7tQmmTfubMklRlK9R4aGceK+9ndCZhsCMr6CJmm83ilxHh8jjlvHC0z2MRmVHrUmm06gwa9hSSj3LLxC2PMI/FiwUp9hFnjPB2/TjNzmAmbyGqHZTWLG53n8kHq0CkrRWQwWYhJdvILe90aoyRbAIg4J69ZPMLeQ1Msdp9KkKvVKrr+jYVEylIFPfNJpYkbaoSDh+/UzBgPt4gMg0gJDDtF9mL0JGbFHMRNyx6KAo5sIUROICNdh6ZOSeXFyDNKSOEhMwkKQt+hb1ookRCaFayoTdrP368mYUfmxXxGRfiYpJokkgmRX6ZMG98wCRwHpEL0JJrVxdAAFGEic8VYSkIhmQ89Er1CYHRJtZyERyK/QTgDxSJRBQp+fjMJ9fxhxcOF3ib1QSjKtr89JMhDDPEtivDxFtu0yAyNNXubSk8x1kxYmZjC6TXoVUY5U9tPokmuUo8ipGLv+iafS69kPAWdDG1ih/ORxr7mQSBjwp7k4YqDETyGwWEubcVs6Q38vshXmaI2RcsnbBuUrRI9qwdhRqpAFXSmWgF2lCCAbtlFxBFjZoeoC7GtaFIl0ALcxKWmPEIs/EFK6qiWW9nGwi5uv0VlK5++ZHopu8aXcEdzUeSaeC/d3hGemd2B7o1QjCr8r1foyC4U4hYASVqi6OSk1Yz7aEGu9I72e/z0X36Oic02tx4+REk5ZIYB+WbiQd+1ZmZY/ZAyDtNpBZGlaLogUCYy7eA5Lokd4x7MCbLp5/c109CIU4P+YEqFlaiLcdNCgDFQkLthiZ7jwmCiU+wPRpUW4ny8aZbC12iMvhg3nbRzH3LqPTUoxKqAkEOLxdPAkCB/h2J5bZ1Q2mjVhAfDKwHYd+4UcanGjNsC4Jizj7GsheXHVO0JFl1JpOnY0XkOtvcAsCEFdeFRaW/j7ctJ6VIWYG0UcLQ5dAQruiLTNObFAs14ghWtxlRhB6EnrBrjiGSVg1FGV7ksOFtUPINCNYZOG5TifHGWiXSVCB17wFhFZjIyXr44A/nJISHfqHoMoJVr2EGTyCzhRtCLBz+3PEb6ORnsGxq6kyH6GsWoz5qd76+IR6JKlGQTXVQHcdM6qqNRkfkkiK7poFSIQGIAvl+gb9oIAaFVxoh7xN1xAKpaxs6gMWSchK58Im7aD0tUaNEfxE2jUvR2imaElLMQEHSxkRhIdDq6ZCL2Ca0KiRbT1KuAIlMRiWYjU4muEgJVotAfqN1GXpw9HOhtUHfqCAQ7fm6xEELQ7Xa/4WM9xBBD/P0jfLzNY+R1MXBXecZxiQDOz85hhiGaafPF0VmsMODqiYfRu3Wq/YgTYpJ9ZFjVFTRd0e0rlH+QoraGJSX3j0v0ZB2lz3O4k3LaXqST5ISv7O+wrbuoVFLVJlh1MuRggoVpZJhRTCHKi6lXKiCjkBGzR9RKwFH0KODpHm7iUlQ+PWETOrkY4mo5Aa75fXRpUPJyYtfPEg6PtJjdcxyAqaxKao5QQOGTUgzrrNYFLSWQToSWhcRxmYLmk2gaZuQh/R1UGvHqj3yKZz98nHfdMsGjM5OUlE2q62RR/vcJO/8s0gQVKibMMZSqYid9hCHoZzpK5bVQzT6OtEHpCtUcjCQ1DPxUJyjmTc1upqGnOVEXCkyRH5teWKRZLCPSGJmmhH4uUuhuTJAY5KpK56t+97qRN+clg0kWKm3jpRnRk2ceSwl2dWixeBr4phJkIURVCPFeIcQJIcRxIcRN38z9DfH0sbC0RF9WYDzjdHoQmWXsWV0i0Q3G9TZdzWWJMXRrHdIg9x8X84u9GS9S8/aQipQdqRgRAeXOGsl8hu8Xsd0eQcOhonKid87OieUcC/T6I+yoAjP1LQIsmqYkzXrsCgYTLNxNKj0Do6jIwi5uFOO5LmNphwVrEi1WWCpCmRlCCBY6C4w6oxSMAkqpb3gG8gVotRFsv0FklHCDmOZAsdaeHDdt6UhdYXqCctRh40LcNB69bPzL4qbDQdy0a26iZ4qGKdEHCkAxU18RN11AT/rEvUmUgoKW0Sbf5+ggblpkGYGe4QUlqrToGQV8y0GmT4qbVvnx3nGrVHpdpHBp6JLRNCQy8i7zNa2AJhSoiNCskIYaI1mHLmXsgbfasy4oyAXormNIg5pdY8vfQkqJ67pDBXmIIb6FkHox8brHitqhm+mk9jqXLStSQ9CycgFjynC4fdRi7+pJimNbODujREqjmdWYy3SK5fsAmG5ItuL9FEU+xeZYfRWFIDMrzAaCbXOHlhYik4jZyGNN5X0JNTHHyWIBq5vXrpIIiLOIUpgrmb1iERmHVI2AuCehJEiFTtts4yYuBSIiaRIPeikMI1eQrTADzabYbQGwYxvoYZXiQGH2RUQlg35RoycUVpZPsNjSBFFVYoYduis1eos2oWVhBz3G1o/jfeE/sef0Wf7Pq7+Hj1wX0zQFBWWTapJg4N81TEEGYGhkkUCYJTLKOEkXZQq6CDKRE2Rz5jhB00QZAtW6QJAt/MQgdPJ66WYacqAgW8rE0fKfd+MirVIFJRRWGNLv5zXYthN66UBN/hrKr6FXAYjjXEFOk/zY/K2TLIYWi78T32wF+X8AH1dKHQauAI5/k/c3xNNAlmW0GztU1RmkoVjR5phtbmMmMRsqZETr8mhxP1k3RcklIKNqjnPSCTBUxLa/gR1Ms230UEIxGWS4/ibaaEDTLzKlpbR7JaZx8ck4W44x05CJcJMwKNLKbKbrW6youScmWMQh22qGrtOm2jMQYow49SmECSXTZ1QEnCnM4aU2bqaQeS1msbN4sUHP8zzCMPy/I8j1OrbfzRXkMGA9zYu0bneoXIibLjioDAqxQTlqs13IFeRK2uOc2DNI08vXB2NNIroCCnmaXsOSDMZaUiUhSBySCxMlbBepMmSvTJoaOHpCH0Wq96lqgo7pUu52CAyBHxaoqiaJNGiXy4hQYbTyYj6R5UWxZRep9TogijR0SQWfTKsCsCVdTC0FYiKrTBpciJsuo6et/HiWdFDQwyXr5suao84oW36uhpdKpSFBHmKIbyFE59ooFH1TcV7PQEbs20rp1EpkoU9kWljVMZq2ziXhwwA4LZ/PpVeC0pj0NfSJB2klgpnNo2QY1LOUJPJoydNk2iT7BwGamhbRN8BSPSa0gK04L8oj6QEeqIxTascgoR579JMOpTAhFRLfcdBin4IeEfU00mpuzetYLQpJAVfE+JpDoucNydLqkEY6moJYL1Du5gSx49poQRVHdoCMDgE1JHpq0tEFVjoBQFMIKGaUnB0iq8zqXTUK/T7zy+e47NwJsiTg0Re+jL980atIRIeWBg45GY1k7mqwDHhYHSYzDNJAsq0LFDYjYZvEkrRRSBEzpxZwRjZonaoQ6xL8gR1Cs/FTg8jN62UhU2hpvjpopia65qGT4iUumSOJNA0zjPD9vNnbsWO68dMgyAMFOU7ysJA4zknwU3zIzsjQYvE08E0jyEKICvBs4I8AlFKRUqr1zdrfEE8fjUYeMzkn8w7ftlXn4Noywq6yYvQZyxocK+5H34lwBsswNXOCE1XBlFqmn2aYwRibuqIqfMaafTJbYRZ8NgKL8VCwVRrhAJIGMesjNnPxEmnDgVRR7PVQ9YSF4Ch6vEw9zXBVygYjKAH1RCNoTxHJlDQz2CPXGNFCtsw6O9QwEoviWP5k/eQRb/83EywuQB+rY4choVXADXpsxDLvlLafiJtulcqkg7jpctKk4VRJkYxFDU4aedz0xTS9Qdx05rbzND1TYGf5+9TIiBIH3RjETdv5jUJ2ydP0jIhECVKzTUXqKCGpNdr0LUhSSS3Kld5GuYpMBEYrf58JWgB0jCL1TotUltnUNFzRR8nce7wjDGwtBhShUSQLFPXMY4cKLgMFuSgQSqenXKLWKgBjzhjb/VxRKhaLQ4I8xBDfQggXO2xLDzTBmtXCDRTVhmKrNoHjtehV6qxU89n0V7qPgl9lqrPAZ7MrGc0EhtKxxrc4H0qK3SNoREwwzpbqYcSPI+VhDg8a9AqpRmqaaFreoLcTFtGsDEta3FudQPMSsoLBpNejlzQpBiG+kwsHBeEjBMSeRlbOibCnezixiy0TUqEjEoe+CcIJLs6j9K0ylt9HS1P6TgHlu0ihMMwAj5AaArtdJNBTnDQXSloIKCpcq4GqFqg+16dfcvAti/suvYHGi/892eR+QAcBfQHOoEFZ6QZZX6MkBZ/mZnSpAMGOyMWSqaBDbOkEgJ4Jns8nyFJJ/7SLr5kIpUCB0h38VCd08tpqZ6Diwbi51ELqfSwy+omDYcXEmsSKQvqZhp4oCmZCKx40530Na4SmFRFCI4lblM0yQZTX6qf4kJ3a0GLxNPDNVJD3AFvAnwghHhBCvE0IUfjKFwkh3iSEuFcIce/W1tY38eMMcQEXI6YLa2xnIySmycFzZ8kqc2ijXRwV8WjxAHPNkOkdgauXMTSHU7UCk8l5xoMKRuqwIcxBg14Hb29eUJZiqHV0OuUa+9HoxxmL4zXm9PN4vSpRLJn1dshqPkvRXoxomcNJXmyWB4lxU0aCtzaFEtDVyswUOmhC0cfOl/uTCjO7qvSiHjvBzt/LDOQLMC7GTbvYQY+2n6uoutWhECiEUjRLFfqhSUlJiuk2ahA3PRY3WTTHKMgvT9MTkSI129RDxbYlKMp86bGaQZK6mGZeNIPB/GWjH5KlGpbpIxKLyGpRFPnxLTdb9Adx0/UgVyCaxXIeN93IpZ0pLVcGQs2k2m6T6DXWpY4pIpxBQlNDUxS0vECHpo0IE0Yyjy1VpWAF2EGPfgFkZtCgQthay4+tU7+oIA8J8hBDfGshWuhy2sjre2SvcHQx97guT0xgBgGaYfFodZJqp8GuyfNY2/sZZYeHxCy7EoVmdXDdhLif4cV7qBrnKBZmOOEK9GgBSx1gXy+jpfWQXk5aU9Wjbvbp9m3MkoaSa2w4JcIgQRV05rq5guwEIb1iBS2JKBoxSZx7lpNCXvf7Rh89KWENGtZEVKRdAFVI0AbJoR2rjlQpbhDhOUUyP/9d3Q4JREQNQUtVkLqPG+VqajcVoINhNuhnNZJJi2DcRQALBy6nqyuqiQ0oEBYeKfYFgqwZiLZOKSjTEyXGBjHTHXI7xVTYJ7Tz4+BgcDNfoNGaxUoyfM1GAHqiSKRLmBko3QPNwkoz0iRDKTAzE6H1MUnxUpsRvUWs5wpyoHS0DBwrwYvz+8PXUn6FEOh65WKTXniBIMdfmaY3VJCfDr6ZBFkHrgZ+Xyl1FeABP/+VL1JKvVUpda1S6tqxsbFv4scZ4gJW19fJEDgVn/v9awE4eOoxwuo4k6V8ef4Rdz/TYYdSL6ZmTrBhC7qmTSE6x5H2bgA2hUZdeFRbDboH8ov3bBpT3Cqg63O4CLaVQadYZE5boBWNs0aZybSNLHdYETODCRb5xXvayAYTLBKiwcPthj1GaUAgVZLbHeJ4jH2HJljo5o0ou8v552k0GkgpqVar3/Cx0afGBwTZRqLQ2yaCDN1uk2YuhSimWa6w41epICimmwC0B3HTa2ZpMMXiCYKMgkR2qEcZO5agKDMUGZVMopIiDhtfFjdtRR2yTMMYxE237E2KIr8RlDudi3HTI4OGRc92CC0Lo50/aIzo7YtJfm7XIzRGWZX574xGedx0W4spX0jTs/K46Ym4zQ5lTCui4Pfo2SBTiw4lsk5+0x1zxtjxd8hUdpEgZ09uABliiCH+UaCSjGily1K8jq90Yneda5ZBCWi6ef3QDJv7a0X2tk4ijQSrnfeJLFFnT6awKg8AMN5SNON5dG0LoZk8NBIiSJDaHg52Es5bywRhXlOSuEvF8gnaBkXHJdGbkCn6cYZydXa1+yiVYSZJbgeLQip6SOw7RIZBzyiRAaEMkXEFU8urV5ZUaBcgK2dYoaKHQ7tQBcCOIvpOgWRA0qUdEYqEGoKGKmLLNnZSQGaCbnahj6RBpAr0VAlp5x5fLc77PCppEZF1SWWNWMWYXFCQdZJOBZU57FanGB8Q5HhAkKeDgGSQgnrA9nEIWAv2YGkOkaajAD3OSLRBs10WIcwiRpISpBoShZVaKM1HRxGkFpP6FokUWHFEIE30FDQrI0hzpf3vIraGUc3jpq0KMssFjKcqyEOC/HTwzSTIy8CyUuruwf+/l5wwD/GPjLNLy3SNERhTPJYMIqaXz5NZJlN6i0joPK7NYlubiCjIE/RKeZHxogVGe3tRKDa1jLrwKXfWiXYrosgmMjvEDZeimAJg0cwbEeZZoBWOsy4rTFUaCKFYtcYRyQoHw4y+sjnr7FDq6xSqEbQHEywKM4xluXppRjkhVHGZub2TLLRzgvyVI960wdzfbwTm7ARWGF60O5Q7GtogbjpSpf+fvT+LtSzL0zyh3xr2fOZzJ5vN3HwIj4iMjKwsqCKBpoYuaKmBpkULUS1oaISQQIJnhBAvIMQjPIFK0A2iS0JQ3epG3dBkV6Oqyhoih8gYMnx2t3m41+69Z97zXmvxsLZd94jwcI+qcItI2u/3YmbXzj1nn33O/q9v/9f3/z6Gbc1yOGZR93HT9mXc9IT99tO4aUT803HTZcG0tqwCQawjWl0ydBJnhsT21MdNp7p/nxusCQjDithEnIUvSPoBmCQv2faPm+X+MynCmDJJwCpMnZCFO+jT9MKywegJp8r/zkHzFG2H7IKCQeA72VUvbbtaLTAo0Ios37GLQJmIggS587aA++k+netY12sGgwHWWsqy/Gc+35e4xCW+GjTPdtA5trLiOQE2XPCNY0sxTqiswQpJML/CLlS8bd/BWQnbmtKG5GbKYatw+38MwNHJbRz6Qif7zsw3Aqpojzu55VF4zMYZZFMxKndsdICpNTO1x1lcIwpfq+1Li7fWfMbirWYvzGnzoPdAntIKg3AK040I+w5y4yZsxkAKSWXYiCHLzA8ZJ3VFkQ5ock8aRVpTyYYJgnObkMkFAsGgCn0HGXB9o2VrJqjYIoDZ6Tk7OibdEGnWGDVHmZpG+6JodcAunxEHBd8Q32Ms/fkQ/ZzHUd1dJJfupSXvm7d5Jm+h5TUa7d1D4qrCSL8mZQ0QZai2ozIB2voOslUlUkHlAubBCoQg7FoqFaE7IHRUprcu/WUJcjhGWL+r+HNDeskUmh30u7eX+Hy8MoLsnDsGHgsh3up/9NeBd1/V613il8fp8+fELJGp5ZG4zeF6SVaVbEzDVO94P7tDWwhs8BRomYYHvJfUCGc5q56QVNdZBTmdcBx0jkH+DI4aNvmYw7hhd56x50YYHB9n/gK9aR9SFBOWpNyYv6AgYRWAsQU3645jrrJKXzDZBYRDh6s2pE3H8WCPq91zjvWMQd14TZcQRHHIw81DBIIboxsAv7KDBYDeGxF1jqp3cJhtNcI4VLSltGOGtmQ5HFGXQ0ZRi2xWACzklP1mySaMCGQNssUKX5jrQKFymLQVRgqaxMdNp1aB0+hmTRHF1BFYoQibDV0bI6Vl7ELO1BLtIhJAVS3roS+UUT0gchVFGFHFMTZUmHLg46ZfpvpVLVZNL8JCrhTPkGJMHmwu4qZL7an8y7hpi2aQb9kECmliGhEhe93xXtJPhpenDIdez3wps7jEJX7zaB5uKGlAC56GO5RxHD2zLCd7BNWWYjBmNTkC4LvZjxDrGwzaT/iP7XeJrCK1EcHeU160Ar39FgD7rcRZw8P0AxxDYhUQW8FO79gFhqArOGpanuNrwURe50GmkLm/+Y60IWxb0t7ibTdMEU3NfrCm2Vi62LJkTC1romZMTYDuWUnNjHyvd/xpWrYuYzP0Gua0LsmTAWVpwIm+g9wydoJzmzHureFGZXzRQbaBr1OlmRLGnsBHTU3jYGgzgnaFVXNUV7CJAiTCSywazShYsSdyZsI3A3Qf/HRYW+hrbW0j/nHzVzkWc4Q4pO4Dp7K8oJP+70kjcEGCbhvKLiB0EPZx0y6EymnS0JPWwFmckKhW4EKHRdIK9eUEWU/oehcLYb0f8/LnJBbeL/nSyeKL8apdLP7HwN8WQvwYn275v37Fr3eJL8Fms8E0NdfxE8yLaI83jp8iwoxHasseK94ZvA6LhrDyXYNpeMCHQ8shz9l2DUG1zwvdMRIV81WLlA3BsOBFFXOlc5zqKa+jORcdz6eKeXNGsmqxVrPpQg6npzw2d9Ctj7C+2tScuuus0xWTbYhQM9quJKsbgrBj3xV8lN7AtZLUNZD4Lf0Hmwdcya4QqQjn3K/sgQwg0wAVDqlj30GYlAmuc6iopHBDJtbHTdsyZBTkBL0l2omasNcs2IX9lp/8TNy0Vog1jNs+bjqaYmVB1DtkmLKmCGOsammCzMdN116iMZWSF9J3K66aFtNJzoaevNtmnzErqjikTGKcFrhdik42F3HTNA6rJpwpf6nf2D3HqClFuCHWPqWpUn2aXu2LpbUJWbljoyOk7dP02hqsYT/xMqiz4jIs5BKX+POE5tGWh7GvFXl0zK0TUK3g6f4hyW6Di1M+nB6xtz7nyuwZcvk6h+5j/h5vc2R8fRhOCjYVrOq7TNQTZu4au3aN6z5Cym/wWulrRYyg04pY7bgiak6Nr1cze5efjGZMekedoajobEvWy8F2w97iLSypVy0kjpyMXbBDt2M6BEIIhLPUTGn8/TjjpmLLgDL0HeO0yimSjLyrkM0IHdeUNAgBOztgJv3aNSzjiw6y1Z7cWpsRR56ESiyqb6LO6hwbTFFmxSIShE7jdICrNV3ouOkq9kQFOKJ2h8Ow10qGgSfLm/UV8mbOsdlDyYDqJUHebWn7QKa4VXRhjGxrWqcInfUEWTW4WNKiKWWMlhD0dqCiEbx0eKv4coKsg/GFi4XAkUr3+S4WcDmo9yV4pQTZOffDXl/8Hefcf805dyl6+Q3j+XMvV7ia3GfrMto44c0HD2B8k3pWMrI5Pxm8wf55xeGyJZQxaTDmg1nMUfeQUZMQtWM/oCdyZost1TWJlI6njWKWS1aTCa+j2JmW5/OMm33ENI3lYLfEzjoeld9EtU+YGMPAdZwwxwnHvFU02ys0skMYzS3xgj1VcT+9wdpmxFYSjD0JfbR5dCGv2G63tG37K3eQhRTIdETbb5sNq+RlqBF1oNlrlyxHY2RpmQZbdO7J4bNgQuxahO6Tk9QWp7xMo9Yat9CMTO8OEY4RMr+Im26qz8RNR2PiaoEpJwBMpOCF9AX4pqlprGaVhTgcXT1nwpIyCqnSGKdcHze9RkUCcH3c9JSFUjjgdrHB6AlFsIbe0aKRvngOa/86hpSs2GKkphMvvZATyM9+qoP8kiBfhoVc4hK/WTjnqB9u+Ng8wTpo0uf87mNPsE7mU5QxqCDknfGYW+sPEBJGi+vMxIofi+tcMw4ZrRlGFr0zrNs7TIJ7ZNFVHgQ1ujshcq/z+tYTvbTtpQ2hd7B40QwR2jLkiO9ND0m2LQSCvXpL2W0Z1waLoEhTZNMwDmrarcQNJUYo1uEK1038RKGUZLagZoL1c3aM2pINA/qXZVCscVKxUC26HhEFJUZYWgwlY/blCmNrBk1G0YfPuX7Sz9iUNPJ/V7aBvrs6q2usmiHtgmUgSAgRQURTaJCCOhIE1qEiQ9KUNKpi3Cr+O/rfQApDePwGWblhGQwRUntpHZAWOZ00OCBsFG0UIhpP1gPbEVnfQRahJ9TnzYhYWxT9bEctQQuQjsL9Eh3kYOJ9kEN/8lJhPl9iAZc65C/BZZLe1wxPnj7FOshGO35Yekn4Wx++QzU5Ym/iic6fZa9zq8iZrQzT8IBVAC/SAaPmPt9eec/hE6GYy5zJesHmTU+iHnQd0/OYLrnKIZKikTzZn3M9eMimnLMxIdeKJUy3PG5vEzWPeav1hPJJP4R2pDt2Fw4WA27FKyJp2agB50xRXcz8aopz7qcs3r4KB4uXkIMJytVYoUjrgLpP02tD2G/OKOIY21nCqEPlPm76efQybrrAupBYri/ipmutcEvNqL8/zMMBkgLhJMJBXaY/FTcdNhvarSeiY+U4k16mcpWGXMY4KahlR1OOmbCkCLzEQgiDWgt0sibqi2vVKawaY4RgpxTX64I6mFKGOx8Ug6NzLVZoYuMX1NoNGfSpgVXgP9sdGeyOP5cgX3aQL3GJ3yzMqsZuGk7tijOX0sXH/NZzS5MG5H0nczu7yjZUvMGHOKMQ/fDBE3fATWOR038EwGw5pHEDnDpHpTP+bOzdbmJ7h7tby4leoEvPVFtRMI8K1kVMOBRYec4Hg31sYbBZwMEuZ9etGFQNVZzhpCS0BaEytDuNnfhjWMcL6naK7PXHY1dQ25Qw88ceNZYNQ5SrQQSkpV+rTgOLbsakyu/OlaKhZsIeaxrXEbcjHIKqAXQNWE+Q456gdiWu9X+fVTVGTencKYs+LMTpgLL0NOmPvjXBStCxJawqKtVQX3uHvyz+CYnq2LYTttuKTTpEKOV9kIGk2OKEAyFRraKKAp+UZy2BbQhNSC0bZD+cuK5HxLpF9h1k098V6NCQW/mlXd9AjzFmxyDwO4SRaFn+bAc57TvIlxKLL8QlQf6a4ZPHT8jDOWLf8ZP22wC88fgeNk64EqyxCN4L7zAMFqimYhId8eHQ3wnXzQOO8rsA/YBewWh9QvWapOsCXqgczgZk4joAjwOJUYpbPGDRHfFYzTmSK1S644m6RtI+4Ld7B4uPtW8eHKaGeuFf70W4x7Q3Vu+cpiHEtlPuvL7PolqwbbfcHt8GvhoP5JeQwwlRvfZperWgT0xFxTl75QqAPFDo2EKuGNQ5zyL/ukORY92IgVyixBiEoAo0rBUj6XW82zBBuAaBIHFQVJ+Nmx76uOm11wqOpeNc+AXqCMtaZeAclTbsKk+Q8yClihKEdehlh1Qdc5MDgkU0JGotioi1lhx0JXXoyfzzYIgUDqhpwiG0gsRV7BhdxE3nkb9x2TKA7QlpkJIFGeflOVEUEQTBJUG+xCV+w2gebrBYOmV4pgxOVtx66tiOZ5imogkizNQ7Vrydvgvr6zj7MbkNKbo5B51C7nnZ3eDkTQC6zncGfjL1tdUE13lj23E/fkLVCDCGummYhCXVNiRJE5x6QaM0RdNhe4u3XbcirWvybISwllTWWKvpKokd+RvwQhfs2jmqlyKMKamcJsoEMnco62tQ3JYgU7Je2raMJLoeM1C+XpXUBCph5FoqYYi7KQjIO4EIDbHYYmzKMMgxUhI0BfRzJLPGYNUEK16wjAQDG2OVvphjc5niT78zJoxaBsWO8zf/Di9e/x7fc7+HliHPRULb7thkA4zUNP3cR1r5BocKJK5TFL38LewsoS3RSFphCKw/3+tqQqhqXO8O1HX+HMm4o7C/jMRiAkAiHQJBSM26+xkN8qXE4pfCJUH+GsE5x8nTpyixQw4N98VdpvmW6XbDBss82HI/uUZRBRA8BVczDQ95L/EEbVE/JilvsFMVhXTsd47h7gn2mmGXj5kmO8rzhJHzXdx7FxHTj9gVc87IuDJfAfAs3ofuGW/WlsqFfBIvGRSa4bSB9Qac41F2jTHeXkw1fbFoD7jz5hEPN97B4mWK3vn5OUopxuPxr3ye1GRGXC77NL3u07jpaMM499VyF2lk4AgLyajZ8iLx73nodmzcASO5ROOLUB0o2Cii6JTIOM4jiXoZN+0cZRtfENEqStGmottdwVpJpg0bOpzo2FOOZTQkqSvKAPJqxIQllY7ZpBmytQRLXwiPjNciLpIR0+0GKQeca8nU1dg+jvRYxwTSgmsv4qYPzIoVE6LKLzi7JAQH276DDN7q7TJN7xKX+POD5tGWU50jpOA0PGd/DclGcDLfJ8nX1IMxZ6MD4qbmzvQeYnWXgfmQ/8j+BVIriVxEuHfMWSuo828SiJJp7bu7Hw3u4cSQPEu4UTqehifshEE1JYOqogkE7S5gEkzZhjl0lso4XKq5vSmxtiNsWzbDMbqtGAUNXT3AIWh6D+Rc59h2hu53voZUlAQkCfSzdWxsStrUWJWS5p4gryOJbsZkcgs4StEQ65DUCXZSEPVhIRsrULEhVWtaOyCSHXUUETUFoq9lsxqcGmJ4cSGxsFLQ9u5JH26gSBQyM8jG0l75R8we/h7/TvuvQiDZugDndjgpyeOQVkkvq6j9+hkEmtoElGk/INgZdB837YCw9AR5Ww+JdIvtSW3tvBSOrCM3+pcY0vNroOk2jKIR2hWfHxQClxKLL8ElQf4a4eWA3g3+FIDT6Ii3nz8GHfNIrtkTK344/IYf0Gv8AN00POCDoWHqzlk3O3R9yIugZihqprkj6HboScF5mXFVWs6bCbcJWQvDo3FHYBuOimOaJmHhUm5MjtkyZKc7jC25VbUciysssuPewcLiqjVp0/FgdJUb7SO2ImFS9YXEBuwdzC4I8ksP5PPzc2azGVL+6l9pPZsRlyuacEhS1xx3/jl1vGFU+qK1ThOsgawLGLVrXvRbViOb88DdZiTPkX3cdKMU7Hzc9F7t0/SCvl5NXUfVpbigl0Qk3sBe7WKMCYiDlgboojUzpdiFKbPlkiKCuo2Ytp4In09miAqCc0/gj/o0vVU0ZLZdYcWEUyUZigKrfXE8kwGR6gBLHY6wFeybDWdMCa0vnMVIIJxiS0a3+UzcdHEZFnKJS/x5Qf1wwweh36Fqk6d864m/AX90dECS71BBxCfjOdfXD1DSES7vcijv8/fFNzj8zIDernSs21vs6XtMuht0bcFKfYjkkKEA7QQ7UVJo3/08qlue93VuJq/yLDUXFm8u1RytCkJjkc6xGQ9xTc0kqGjLmCYIyXsP5EY22HbqLc2ATLRULiCJHGHu30thBkRti9EJg11v2RZHyHqEEh1aN+xoGEpNYDVrJQic75qvnEBmhkSuqO0Qg6CNA6K6IMzP6DBMWomVKY08ZhkJEheAEHR9M2MjJL/3x0uUgLbUzL//r3Lwwd+k7Qw2UOxQONcfV+R/t9aaoCe6Oggou4Aq8/rn1Gq08euaBJLeLnPXDAjCjtaUCGepTN/0yVpyE3hS616aiP48gr6D3HYvrd7ynx/SCzNQ4aXE4ktwSZC/Rnj2zMcFX0s/YW1HNHHCtz65B+MblJOCmdnwg+HbTF/UzNcFSgQMgzkfTAOumAdEnSaqpryQAfsiZ7bY0e2D0obntWa/FJxPZryBYuUaTqYRN9rH2EUC1tE2MJsteNS8gW6fAC8dLG6wTpZMdgFCzei6gqxqqGPNVbvik+Q6SdOhnMFpgZSSh5uHaKm5MvB+y1+FxdtLqL09krqiDjPSquDE+LhpHW8Y9cV/+TJuulOM2iXnPUHeb5d8FNz0cdN9mp6TAlGATVbMa8ciEiTWP88US2MSgsBvw71M09O7FmMUUVDTGUkXrhgJr0Ubn6/JE4kxjlm/fbccjcEJ4oXX4l0RfeKTTpmtV3RqxolUJKIA55/nXIqLNL0mTHGV4cBuOXFTkmCLMi3FAIQNWbkR1cJ/f/aSPc7KT+OmL4f0LnGJ3xxsY2if73jSPCe3AU16zO88dZhAsOndeJpsyL1hwp3mQ5yD6eaIidjwZ+Ia142DcME4dES5ZdteYxQ8YqivcOJ2qO4ZAbe5u/OkLHUKqyRRsOWKqznpvEf71N3hw0FGtva1LQwMUdOR9kMc21GMaBoOgi3NTlFFigW9BzIS1w1J+o5qIjtaFElsCGtLZyTYmMi0tGFKkm8R1lKkGe5lml5QkYuKKYLcjai0/Zm4aUss1tR2TEGCiRVRXaK6lrWsmXYBiAgjC7aSizS9TgqsEcQaZAuRs5ha8r3gd3AMSdotJpJsAHobuG0/oNdqje4JsgoiShNQp75Gp1aieoIcOHXx3rdNRhAakmhLIirK1neQZdpSmgCcgXrzC78PLwnyS6s3zJZV1+E+S6qF8DKLS4nFF+KSIH+N8OjpU6wTDCY7/rD8ywB8870fUU2OuDLzF8oPht/gtSJnb2WZBPvUSvB4OGTa3Ofbm2tIFCf0A3qrFbs3fBF52Dmmq4A82+c2krp1PDqccrOPmO5qwfXdOXZa87B6C9U+ZWIMIzqec4CTjlmtafMrNKJDGsVNTjmQJR8M7lA3isx1KN+s4OHmITeGN9BSY61lsVh8ZQQ5ONgjriqaKCWptyxrHzet4g2DyheZ5WhMWQcMnSQz53RRyFYM2G8WPAr2GMjlT6XpycbRRSvmjeUsFAxkT5CdwHZDEv0CBxdpemGzxVlFGJYom1JFCwa9o8R4vWKbCEAwL31nYJdktEFAeN7rlaNeNyg14/WaJtjnmdRILJNuA06wUh1D7R9fRQrZdhzaDSdMiZKaLF+zTR3KhKwY0a78rsJesvdTcdOXBPkSl/jNoX2yBQu5KDkmwoTnvPncUkzGVNbigM3+DawQvKXfh+0+tfK7Qc/MIbc6g9j7BwDMz8cYQjq5Jhgc8t6gQWBJzB3u7iwdlqz1hFRGa/bCgpN2CMIxcTf5/nif8doT4rEr6WxH1ksUdoMM2dbMwh312tBFlhVjKlkTNiNAMTQ5whgiaQlkQxQawsbStorIaQLbUcUZ0jQkTUuRDDClX4N03FLg46bXdoRUBUlPLrdWQAhBsKK0Y+/KE0viqsLJiI1oGHcROHAIShzJRdy0pi0UI+XInSZWLTjBmfCd4KN6SxspNjiU8zuBuXJoEdBqjTJ991bHlEZTJ57cphZkT5BDGxLqLQpL3qWoyDAd5aSUFJVf9ERiqF7aeHyBNEL3Eou2XTGKRphuQ+cgNz+TeJpMLyUWX4JLgvw1wocPHrGJJohDy4/NbyOs460HH2HjmGvBglYo3g9vMwrO0VXFLL7Cx0OJFZKueci17esAvFCOmSgYr0/J72qslTxwJemLAZG6iUbwwoVssowb8gHL5pAXDLhar5DTFU+6W8TNI77VejnAYzyRPBKG/PgIJyCXGXfDc4aq5TjaZ8GY0GgG+744P9g84NbQO1isViustV8ZQdZH+0RVTR0lKGuQW08sdbRBdBFJ27EcjllWI8ZCkFlPFtdiwl675Fk4JpUrhPxM3LR1dGrNrHacR4JMC4xsGVmJ60ak7phKh5SJL4BRs8ZY3afpxZzFJ6TOTyUn24Jt6jsUs37C+mVYiGgFpokZhhtcP72e7EqacJ+TfmjkqH5CYIdstNcD+t/3h3m9PKdD4wLFaLdhk4A0MQUpcuMJ8kF6QNmV7Jodo9GIpmmoquorOfeXuMQl/ulQP9pSUCMUPA1zksYyO4bz8R5BtaHMRjQjXxu/OX4XNrcQ9j02NqHoZux1AWLvJwBkL14DoOhahI75ydjf/Abc4Y2t4Wl4gi69zWYrSuZRwapKCQYOKSx/PDki3LUQSabVltoUjGpvcZb3BHkcVjTLBpE6clLyYEfQjolFQ9SWqLYhUI5pvAIgNoamlMQuILQdeTJAAEndkCcZbenrmujDQnzcdEosNwQ2Iugku94LWcRLWpewcyNEBFFd43TCVnRMzBDhSpzMKDDEF3HTAV0ek0nInSYVvmauhZeWXalymtjHSivnmxgbBaFKaLX24VYOrEwpTUAb7wBBbB10vkERmQipSyIMeZeiY8PheEvc1RR1DM4hk4626Qv1F3R+P5VYeKu3rvWP/TkdcnoZN/1luCTIXxNYazl//owkOEdGjofyDjdWZyR1zc62zPWO97LXqHcSGz4C1zCPrvBOP6C3qh+RlLeoZctKOvasYbh9QnfTkucTonRDtUwZOR8k8Unsi8gtPEF+oqYcJFtkUPNEXyVpHvDdXhf1kQIcHKWGeukJ4km8z5WBlw8UImLJGNVlXL89xTrL4+3jV2LxBhBeOySuK6rYE9J0pZHWoeMVjRswaGuWozGLas5MOiLrY5jXYspes+Isyvq46U8Jch1oKHJmTcc6lKggpVUFA6twJiPsTtnFCUVPfKN6je0igqAm62Je6FMil6EBXTWsB/48DcoY5TryMKZKYmygMcWQKN7iIn95B0WDVRNOtF/YruePUIwpwg1Zn15a9Wl6V2pP9q0MGe42rAKFshE1ISr37/MwPfSfUXFyMRR52UW+xCV+M2gebrif+q5kGT7jjacO4QSPDw5It2tMnPFsdMDB5oxxtEFubpHZj/h99zsMnCQgJJqfsmhhV3wLLUoGla8vH46f4Yioo31e3xrvYGFAtA1la5hFBeU2JBpEOHnMeTykqwwm0xzuduy6FcOqoQ4TrFKIpmIU1HS5gpHECsUmXEE7ZqgKRNsQNA1KwjRaAZDajq6UpESEzrDOfFc4bhqKZECT+zon4oZKNkyRLGxGJj35y6rwIk3v07jpGSq2KGtBRRQYJt0AadcYOcOYFs2nHWSzHRJJx0YohrKXpeFr3lFd0ca+kAbWN3B2GiKZ0inlZ0o6R6dSGqsRcocIB4SdxfbSh9CGCJkTYilNjIo6rgy2hFVDaRW6c6jI0r0kyF/YQR4CkrZdMo7G1K1fH1c/m6aXTC8lFl+CS4L8NcGLFy/AdNzmT7EIVvGcbz55CEHGY7Fk3y35wfBtOG+IG681nYdXeGfUMXQblvU5YXWFF0HFQNZMyoCkOkXtlSyLIdfCluVmxBUyahz3B37r6Gb3gLIcsyDj6nyBA54nezjznG9Uhq1LeZAsGJSawaTFrXwBe5heY9xvA4pOYFGYZs4bb1/hJD+hNjW3xj9NkPf29r6Sc6WP5kR1e6EHnm81wvghvdKNGZqK1XBMVY4ZhjWqH5RbyAn77cLHTYsSpH1p9U6tFWorGDe+01onE4zKSfo0PVdWFGFMGxpanRBVC2zji+1cao6Vf41D02FbwWLkC6VtDxixpooDyjjGBgKX92l6cd9Zqb190Yu+g3x79wyjJhTBhjjwz1P1Q4J7tdcWO5swzDesdYIwIQiBbUvoao4yb0F3nB8zGo0APwB6iUtc4tcL5xzN4y0fm2cYJ6izY777xOEEvJhPPdkMQj4YT7iRfwxAunydI/WQP+BNrvQDyONxSVHCsr3Nvr7PpDrEOcuj+H2E2CdPNVdqOA7O2IoO1ZQkZQ3a0WwCBuGQJlgBsGk7XKq5vs3ZtUvSqqZIfZ1IKFHC0ewUZuzr6zJa0LQzRqoktDVB26CEYz/ydX1oW7qtIiMh6RrWA0+Qk7oiTweUVQdWXcRNTxAsTMJI+Vo2rKJP0/QCr//dmSk69g0aKQWVs4zNEGk2WLWHNjVFGCCc7yC3u5RQwEpKRr20Qhj/fq9U7UXcdNSOycqcXEsildBq72QRNB2d6udLTIOIBgRdR2U0At9BRhcEWEoTMQ5qQmXReUspApSFIDK07ZcTZCEkQTD2YSHRmKpvenyuk8VlB/kLcUmQvyZ4/PgxAFcGj3jY3sYGmm99+CF2dhuulGSu4ofDb7D3omJ/URPKmEE44915yA3zMdpIomrOsVTsix3TZY6ZgQo7ntcBVxrHWTLjdRRnouXFRLDfvCA+tzgnWdqEW9NnrJhQqgpjK27VDc/EdZapd7CIRgZXrknqlgfjq1xtHtCiGPeDaG035dqtQx5sHgA/7WARxzFpmn7OO/+nhxpFBDKminwXZZpH0DlkVFCYERO7YTGaYMqQUVCgCk8OX6gJ+82SXRQghI+btn3cdB0oxFIw6vy2XB5NcbIgtP4SbEtDHsVY2VKHI5LqjK7w3dmpEJxI/xqvdQW1DVgMIp+mV82Y9ml6ZRqDcrAN0fEa2XeQTePT9F70gyOv75Z0ekoerkH616heGvT3wx+tGzDcrTFS0faF3XshP+cw+7SD/JIgr9frr+TcX+ISl/jlYRYVdtdyZpacuhQbP+fbzx31OKXE7wqtZoesIs1d9yGuiRjWI8Zix0/EVa4bh4lOmISOeGfYtteYBA8ZiyPydktrP0HZOfvOE8yShko7QldyWDUcywxnBXvyiLO4hsZSW3CZ5ua2pHMNUdOwHY5RXUumG7ouwxmJeemBHOTs2jkDUROYmrDrkDgOQ79jFTcWs1ZkLkRbS94PHmbljiLOKE2JbMboyMdNJ8Dys3HTVcy254Yv46Y7mxH3u5wCR2scmU2I2y1Gz1DdjkUo0Sic1nR5ghZwJhVz6Z9DGV/LjxqLC31tDcyIYb4hDwNCGdNoiQDSssII/5ikA8IM3RNk7bwG2ckKjaN0ARPR4BzIjaGSEcpKwtBSmn7L78u8kPWYrn3pYuGP8+ecLNKZd7H4AkeMrzsuCfLXBO/df0ChY+JZxfeqvwTAt977IfX4gKOxJzc/GHyDO3XOfGWYhUfkCh4OR8zbT/j25jrKaZ4LzVzmzBZL8rv+Yn3Ywt5Gsx57B4uqa3m2N+CmeEC5HkNriOuawWzNg+Lb6PYJwjmutjUv3G1W6YLJNkDqKV2XM6gbijjmSnfGo/CISeW3tJxQRFHEo80j4FMP5LOzM+bzOUKIr+RcyVAhkzFN5N/fsE4xnUMIRx2ETLsVq9EYWTqmekuw9aTyeTBlaAqM9t3YUG1AeZlGrTX2XDO2KwDKcIIUOdL5olkWPizEiY4qmhLVa7qd74hPFbyQvvNxjYadiLFK+jS9PiykCCOqJAHhkGvQyZq4N93PuwCrxnRCsFWKW/WOJpxSBjsK5S3fDB1WaIIWpLNUbsyg9xotQt/J3jCA9VMO0gMEguP8mOHQd3MuO8iXuMSvH82jLQaLVYbn0uFkwbUnjvVojmkrOqXJ964B8HbyDmyuU6hPAHhurnCr63Dzvw/A3vkIQ4hVC+L0gPthhXQVsbvJ6z3DTGyIk4I4WnPV1hw772Ax5zb3U4XO/YCeSzVXVwXaGJRzrMdjZFsxDmq6KsMB7Wc8kLtuTkqLbGq0tQgBB+EZthYoC12hGLV+HXiZUDeotnRByIrax02HxUXcdOEm7Ik1xjYM6uxCg/zZuOk48s+nXIvpnSamdYnVM6RZswwFERqnAroiRAKnSjLvO8hB3+zYawQu6GUe3ZC02rKLU7QMqfo5kGy3o/OlnrSR2DBBNg2lCQitIDIRrapRzlE7zbhuOakGBK3BSIW0iigw1L8kQQ6CidcgR97mDficuOmZ7540+Rc+19cZlwT5a4JHDx9SRglyz/CO+y3ipuHm8yc4rbkSLMllzD15lSw8RdUFs/gq7w0FTkhc/Qk3Nj5d6aRP0JusXrB7I8Q5wX1XMjpN0cENhgjWrebZfMpN/ZB1tU/eBtzKz7DTLY/L19HNY651hgjLMftYaZmWmqY4pBEdqpPc4JR9St4f3Ibakdoakfpi82DzgEQnHKTe4/KrtHh7CZmOsdLgEGRVSNP6u+wmhP3mnHU2QDSGKG6RpSVoW56FEwAyWWBdRCJX0HuE1oHCLQJG+G3DXThEuhLhJNpBUQ7Jw8Sn6cVjwnZDu/EWdlNlOevtg47oWGn/nJXyaXpTFn2aXoywlmBpkKpjz/jO+1kyJqtqFAnLQHLYlVTRFITjWTBFCotzFXU0wTQBe3bNRowZ5i89PX1nfsMQNs8IZMBessdxfozWmizLLgnyJS7xG0D9aMNpsEMIOA/PufUCgkZwPNsnKdZU2YjdcE7Uttwd3UNsbiHMe6xsStHNmJkIufc+AIPTOwAsuwY5OODdoa85WecdLCrRMmz6VLdkzX5Ycty7REzdXd4djZkvPUEOtSWpDWntiedmlOKahllQ0BQhdRix00MM0MoW20xJrMU1DdL6WrsXLaDod9gKRdp5vaxVFhCkfZreaegImjHJZ+KmSybsizWNa4nbEVYI6gZcb2tpbUrWx03rrkK0/rhndYVVM3DnvRdyBDqiKxVCwCIUhNYiQ0PcFHSyYtqqC4mFMylxvWGXpgipqV+S4mJH2zcsokbSBRGyrWisJrSW0EQ0qkEIR0TNqKx5lE8I6Emti4gCh0XS8uVpel5isWIcjZE9QV7+rAb5Im76Umbxi3BJkL8G2G63dPmOG/IHCAHPwpv81vOHKOd4Zkvmesv3R9/Cri1SPQC6fkDPF5DT6iFZcZtKNqykY98aRtvHtLcteT5GpmuqswFjPKG7FwmslNzkAefdFR6pGVftCjVc8cjeJG3u850+v/NhP/V7RViKkyufOlgE50x1zb30BhuTkFiIp17y8HDzkFujWwghaJqGzWbz1RPk4YS42dIGA9JaUnSenMuo5KA3Vy+URMcGkUuyJud55LuxQ5Fj3IihXKDFFISg7OOmx8FzAFZhgOgtgQbWUrQpRei3DsskQ3cl3eoK1goGgWElOhyWfQWLaERS5JQB7MoxM87Jg4xtOkA2lmDli/3Vvlt9no6Zb1YIOeSFVswpsH3n+LlKCKUBWqpoQldK9u2aJRPCpvdSznya3pohbLx/9WF6yEnht0BHo9ElQb7EJX4DaB5t+TD0N91N8pS3H3ty+fjaIelmjQxjHo72uL5+hJIWvb5Dxj1+n+8ysRJFQDg/Y93Csvg2WpSEhUAIyfvjUxwSKW/zxtbwMHqKrDU4Rydq5mHBos5QiSUSKf9keoXBxteeEQXGdqSN/3c+iJBNzX6wod0K6lCwYEZ34YE8InUNXWOwotdFJxuUX4LoCkXU+LobdyWIhLTwO5/LCHQ9Zig/jZtGD5mQ+7hp44ngy7jpSGzpbMYg9CKUoK2wrf/dWdX5uGl3wjIQZC7GaY2p/TGVqfBDd7Elqmoq1TDqIpCCUEBnEoJ2yyYdIKWm6WVtWbGjk57shq2miUJEU4FzhK4jtBGNbJBY/or8MRJ4WMzQ/c2CczFhP0hd/jIEWU/o2jWjcASuRuO+IE3vclDvF+GSIH8N8FJ/fCt+hzMzp05SvvvxxzA45Gy0YN8s+KPxb8FJSVJ4AjcPr/DOxDJ3L1g2W8LqCidBxUDVjEtNUhwj9ytWxZBrYcN2kXHImBbHJ4nferrJA3blnBMx4upkiRCOR/E1ouYB32n8xfphYBC9g0XVO1i8iPa4OfLDHCs14owpQRdzcMN3Kx5sHlw4WCwW/uL+qgmyGk8/EzdtWPVx0zreMC48ud9GCqkhLBTDZsvxy7hpclbuCmN5jrqIm9aIjUSlZ4wby2kk6JUYTEVL1aWIwN/hV7FP05N9ml4SNFTWYcItUyWpdch8saLs0/TmrS+WL6ZzZCMu0vSuOv/zZTRif7XAyAknSjEgvyDIL6Qm1Q3gqKIRtnDs2x0vmJKIFcIadmMQNuDcTWiWniAfZUcc536I8pIgX+ISv374gJCcx80xOxvSps/5nWeWNgvYBgHSObp0wL1hxq36QwAmyze5oh7yB7xxkaA3HldUpWPR3mZfP2Be+pp1P72Hk/ts0zF3d5YH0TMqYxFNza51zKKCYhcSDDVWLPlguI/KO4gls3JLYytGtS9yu+EA2dZMwop63WFix5IRlayJXnogdzlhZ+l6t50sLVE15AhsJ1HNGThH2lRYlZIVntSuIoWux6RyB1hK0RCqmMzCTgrCPixkawUy7kilj5seqJI6igibHGp/kzFrDFaNsZyyDAUDF2GVpms8Oe0zUVCRJagact0R2gThLFoLGhuhuy2bbIhV2qeoAkmR44TDCYlsFHUYIHAExqJtS2QCalEjsPwN9ScUKmDdJaheR25NglIgpKN08kvdJ3Qw9kl60dhroKX9fIkFXDpZfAEuCfLXAH/28Se0UjGZr/mD8p8D4Hd+9AOa6Q32D1coHH84+ja3zmquLDpSNSLSGe/uJVzv7hEaTVTNeC41B+yYLXPcGHTU8ryKuNo6zoMpb6A5ER2nI0NsSvaWC4wJOHcZt/ee0qE4Scd03QlvVh0v3Izn2THDXDOcNbDyBe9hdo2x9pO3WEFLiG1nvPn2EbWpebp7ymtj79f5VVu8vYSazUjKJU04Iq0bTvsOsvpMmt5F3HSrGbdrznqCPLY7HrjbTOQpUvqK2imJ2IHLVuzXjtNYEPXdgblzNF1CGPZbhImXNASbDmsVUVhhTUAXrhnLPk1vsWKXCKxx7FX+huR84klvfN7rlfsp7lzF7C8XtHqPp0oRicp7cAJnEobaE+o6ihFVw4HdcuxmZGlNVm7YDUDZiAUT2oW/2TrKji47yJe4xG8Q7dMdWEdBwTExJjrl7lNHPp5ROk+GTvavY6TgTfU+bjtH4ZiIHe9yjZudoYyfsh860p1h015npu8zNgcY23Ic/ATpxnSJYtrCabBgp7yDRVw0BMpQrwPSOMOoMzqpqGqDyQL2tzl5t2ZYtzQ6pAsCRFszDiqaZQupo/iMB3JAR2IKkrajCUOEMIRxS9Q4Xmhf82x3jjaOuG2wQUp2ETcdIpsRUliCoKYUDQMdkFjFWkmiz8RNq9THTTd26HXQUUhUF+jc18ppI7BqQCtOWESSxHnNdduTSxf3jZLAoirDNrA4NyLsSpQW1DZEmC2d1pRxeNFBjqtezhFIbKfIY0+9ws4Q2hKFopWGQNT8F+SP+DC6QqRa76GMJ8gAKjIU9pfsIHcbRqGX48Wi+wKJxSVB/kW4JMhfA3z88ScsB2PUnuGH5ncI2o43P3kHkw64FZ/TIflh8g2uqTXDbctefI1lIDhOR0yaj/jO6iYSxbHwCXrTzwzoPepgvlasplPeQrEzDSfzmJvmIe1ygDCWphVcmZ7wtLmLc2c4DDfqhufiJufpM2bbkGjceQeLpuXh6CqH7T06JIO+sDTtPndev8qD9QOss6+cIOvZnLgqqcOMpC55aiTOgY42jAq/bbh6GTdtNaN2yWnmj2HerrinrzNS59ATZAAq6CJPkM8iSSz980wd2G5IGpzigCLt0/TqDdYqwrBA24QyOr9I05ssV+wSCQj2+zS9dTak1foiTW9fr3ACnJAM1lvq8IBH0n9uh/Ux0gUsdcU48Oe4jATCOa5X52zIUFHHYLdml4LsIrZkuLUPCzlMD8nbnG2zZTQaUVUVTdN8pZ/BJS5xiV+M5tGGnAqh4FlQMNtYBmvB+XhOUG2po4R66i0ZvzX6CW5zi1x4vfGxucqt1sDMJ+jtLYYYIoQ+ZRDNOXU7hD0nMlOudJ6k1a6jVhBTsF82nOkY2ypmeo9duAPnt/Fdprm+27Frl2RVTZF4pxvd1gx0Q5srGCmckKzDJbRjRrpAtg1x21HFMVHUxzG3hlMd0mhw9ZrASaKupQuSC4KcJ5/GTQdhxZaaKYKKAYW2RD8bNy031HZEQ0AXK6K6ICjWNBimrcKJhFa+YBkIkt4LuR9BIYj6P7WByrHSDuPGJN0OAkHuFM71xD2MMFJghCDsa2MQKioTUKb+31FnCfqIaQf8RfkeI1HyY/0aoW5w1nfgu9YTZNKW/JchyIF3J0p7hheJ5nM6yC8lFpca5F+ES4L8n3BsNhvazYor+gOEhCfhLb55+gRlLUVbMddbfjJ8g6pQ6OgRmJL9+DrvDPzFVNX3ubZ9C4Bj7fqI6Rfs3ghwDj4xFeOTDBXdYoigqhWP9qfcDB6wLefUteDW7hQ7LbmffxvVPiJwjoOu5tTdZJusmW4DlsrRogABAABJREFUVDCl6woGVcMmSbnWPudheMRh3x21LmQwHHB/fR+AO2M/UHJ+fs5oNCLs9btfFdTBHnFdUUcpSbXjvNOA8HHT5adx01WlL+KmqzihIGGvXfIg3GMgFz+Vpic7Sxes2ascZ5FgqBwOy9RKbDcis88pg4gi8e8lqldYExBFJYmJOYuPSfvUwXSbs8l8d2LuZ/HIo4QiTcEoTBOThrtP/TnzCqv3LqzerlQPCeyUXbhhGPj3k/en8Frp7ZGMChlvN6wigTIpFTFy62UVn/VCfhkWctlFvsQlfn2oH215mPa62/Apbz311/Gjo0Oy7YouGXA+3GO+WzFLVqjNLYR9n6XNyLspYxsj9j4AIDv1krWlrVCja3yQeKeGrLvJ3Z0naUmXgBDE8YqrpuG5893JA3eLp4mFxtI472Bxa1tQ25K4rskHE4SzJLIAFF0pMRNfbFbRgqadMlJFb/FmaeKYqN9Nm3Q1ZypjnQFVTmQVoW2powzd1sR1Q54O6Pq4aRW1FKJmhmRthwhVfho3bQQkEOplHzedYmNFVPuGwlpWjLsQRICVNblwxH3ctJEC2woSDZ0TRMpgS8FCCywjknaDDSVbBLYPENlFAQhBozVBPwSodUhpAqrUk+LEKnQfNy0E/Avqj1i4AX/q3iQMDF3nf6+pemaeteQmgOL8C78buk/Tc2bHIBigXfnzNm8XEotLgvyLcEmQ/xOOT+55Qnk3+D5LO6FKB/yFTz6GaMTjaMmcNX84+g7uRU3Y3gMce9F1fpzmCGd4UT4kLW6Tq4qtsOwbw2jzmOY2lOUIkawpzwYMxXUAHmlFniTc6gf0nsgp1+slcrLgYXuHsH7I602DFPCUCQB7laLJr9KIFt0JrnLOgSt4d3AXXRlC19LP8nFvfQ8pJLfHt4FPLd6+agSHL+OmUwLTYHOFdBYdr9GtRhvDcjRmXQ8ZSUFqvCRkI70X8nE48nHTYnDxnJ2SWLNhvzach4I0iGl1wcBosAlBc+7T9DKJQ/q46S5EqY6RDTnRp0Q280MiVcd66Lce42pC6nbkUUyZJNhQYYshYbK58OdUVYtRM06U7yDf2TzCyRm7aEnSh4WUvSj6sPLvpXU+LGQVRCgTgxC0bQVd/bleyJcE+RKX+PXAOUfzaPNTASG//cRhA8HpdEKc54gg4uPxlJvbjwCIVnfIxH1+n99mZiVSaKK9c/IOXuTfQYuKOnfIeMz7oxUAWXuXu1vLRpWM+uAila3ZD0qOO088Z+51PhpGjFefWrxdWZcoY9HWshpPUG3ju8ftCJzADn1B34U774EsK0JTEypPSbKwH5qrC1ZuzDIDW9bELiCwhiLOEM6QNC1FMqDt3S5k3FDRMkOwdFkfNx0SdIqdfTlovaRxGVs3RMQQVxVWJ2xFy8Sk4FocASWWxL2Mm9a0hWKkHYXVJLIFJzgXFaDZr9e0kWKNQ+GlDDvtX6/RGt3byIkgpjSaOu075FairO9wKCf5S+In/D/N77HuRgRhR2Vagqah6W8ASDtKE0C1AvsyhurnEWjftHjpZKFs8fNDejqEcHApsfgC/FIEWQghhRC/I4T4F4UQf00IcfCqD+wSXw2+/+GHVDpgtr/g7+b/PAB/8U+/Tzt/jeHtHZFr+ePxtxkfV+wtcwIZMQ73+eGB5oZ7xM40BNURJ0HDUDUMq4C0fIE4qFjlI67ENfkiZd9N/YBef+Hf4WM25T5P5JSjwQqpOx7q6wybe/xuf1d8X3iydjWw7J5exQkoRMbrwYKZrnl/+Bp5G5JZSzD2j723vse1wTUiFeGceyUWbwDB1QPiqqKK/KKQrAIfNx2t6dyAUdOwGI5ZVlNmwhK7l3HTE/abBedhQiLXOBHy0obdp+lZpk2FkYI6ntHpHan9NE0vD2OsamjCjKha0tVeorEnFc/VConialdhOsF5v8iY5ogZ5xRxSJEluADsNiVIVrikf+7aYfUeJ30H+c3dGW0wZxeukNIT3Kqfsp73AyuNGzLMN7QyoOulHeve6u0ovUzT+/OAy9r89YRZ1dhty6lZcuYyXPKMt585ysmYoq84m+k+izjgNfshrg3Y277O1X5A78hIHJbJsKYuHefta+zp++ztPOn9ZPAEKyd00VUfMR09RrYSrKFRDfOw4LQZIANLyow/He8z7wlyGBrSylw4WKwnA0RbMwkqujLFCUGVeclAoQvabo+MBt1WyMDf9Cehd6hIG8u23WedCUxpSYgIrWE96JP5+g5yU/xs3LRgYdOLuOlBFV6EhRD5OrWxM2TsCLoOF0Ts6Jh0Q6TdYOSQEkPs/PE4pTF5RiZhhyaVXiKx7p0zrlY72ljTAApfY3daEMiITmsfaQ2gEioTUCf9+7MgO99BjmxIpSz/jvnPk3cpOjIU1hI2DWXR2+tlLUUXgLPQbH/h9yPoO8htu/JOFnb38xpkuEzT+xJ8IUEWQtwVQvwt4GPgfwP8TeB/BPxdIcT3hBD/uhDisgv95xTOOZ7cu08+iglmhj9x/2mSuuGtD36EGYy5mflO4fcG3+FuV3CwNOyF1zBS8O58wvX2AyZ1QlJPeSo1+2yZn+fYsSNIGp6XMTcax1k45w00x7LjxahF25brxVOaJmHhMm4c+C37J4NDRPeI36oNjdN8GJXoTrA/bKmWngAfR/vcGvuCsdIvHSxCpld9J/be+t6F/rgoCqqqeiUEOby6T1TXF3HTs41CGoeONz5Eo4+bzsspw7BFNT8TNx2FSGERqsT2CUp1oBFLyaT1spEimeHkjrCPm24qRxHGWNVSR2OS6pwunwAwlZITtQLgji0pXchy6NP02nLmrd7imCJLQTrEKiBIlwSBAxx1qzBqRi4ltZTcLrc04ZwiXFNJr0XraLFCE7cG6SylmzDc+fdVhH5Be0mQ99I9pJCXYSG/IVzW5q83mkebi4CQpxK0yTk4dqxHe7RdjUNweuB39d5O3oX1NSq9YSp2vMt1brcdu/ghBy8H9LrrzPV9JrUPJ3oYvwtizjpNubuzPAqfUViDrCt2rWQeFeRFhB5JEIY/nBwRb1sQMLIl1nxKkHfDCOqa/SCnyQOqMGSrxhigkx22mZJaC3WN7UW+cbTFFBLpYNvOWGVA4ciIiWzH5oIgV+TJkKpuwITIuKYWLTMk5ybzcyD0BLnvINvw5+OmhZAUWMZmgDRrnJpjbQvSd26tDjDbIbF0bIRiIL0EpXSepF6pK5rYr2HaehncVjkimdJqjXAOYR1Gp5RdgA13oCJiYxGdl3iEJuRH8gofupvkXYqKDK2SRHVN0RNklXbUL+Omv8B94oIg92EhrluxM5b6Z7vOyfTSxeIL8GUF9H8F/FvAXefcf8k5999yzv0rzrnvAP9VYAz8t1/1QV7inw0nJydQFdwKv49F8Dy5yV94fh/lHLum5Eiv+PHgDTZVTBY+QzU5+8kNPsgclQoZ1u/x20uvP34qFAdyx3S5In/DE7r7LeyvNYvpjLdQ5Kbh2V7ErfYhdhEjjGNrAm5Pn7Iwc4rA0Jotr5ctj8U1zrInTLcB6ayB9QrhHPcHN5lpbzVnjSQng27M62/uY6zh4frhKx/QA1DTjMgqql4PPN+G0IGKcgo7Zux2LEcTTBUxDnbo0hPJEznloFmQh77zEMgdTkc+blor7JlmbPxjd+EYJXafpunlKXkUgzA+Ta9Z0W58Q3CqHCd9mt5N17CVKVYKatlRFlNPkMOEMk4QGPTSouItk64FBCudEliJImKhJde6kiqa4YTjaTT6ubCQfbtizfSCIG/iz4SFrB/7sJB4j5PihCAISNP0Mm7614vL2vw1RvNwywu9vQgIeeOZQzrBs/mcLF9SpQPK4QFB1/H6+CPc9jaFexeAk+4aNzqLnf4BSsDeIsO4iECfMA6mVKZizcdomyBjRWphobfsVIduS4K8IdEd9TogSlOsPGURD6A0EEsmxZbW1gxr38neDVNkUzEPdzQbRx0JzpnRCoNwvQeyNXR1RxPE4BxBvEP0XeFVPWedgSxhQExoOtapv2FPq5wi/fm46SGwMNlF3PSoTLwGGbDaSxoaOyKKPIkXQG2d7yCbDUbP0V3JLtBIJ3ya3i4hErCSinGfpuesbwoc1Q0u8nVc2yFxXbHTklildL3VW9A6OpXQOoUQOSIaEBiL7Rrvh2xD/r58mxBH0cWoxNBoRVg3FG3gGzSJoW382vJFnd+XBLnrJRamD1k5bz7HyeJSYvEL8YUE2Tn3N51z/8C5nw/rds69cM79b51z/5dXd3iX+FXwx+/4gngneZd3q29jwoD/7LvvQZBxnJ0zY8MfTH4Xd1IT2Q8Ax158jR/2MomT8hMOdt/AYjnWln2RM10es/1miLWSe65icJyh4tsMEJSV4sHhjNvBJ2x3c7oaruUL9CTnfv47qD5i+mZT8Zy7LNJjptuQYKBw1ZJB1fDJ5BpX24+o0cz6pKSmOeTNt6/xdPeUxjYXA3qnp74Dvr+//5WfO5kGqHBA3RPdUZViO4dQhlJGTLsVy9EEUTqmwQa99Z2EZ+GMSbfDaotzglitQXiZhE/T00zwlkK7cIggRzhJ4GBXDS9inat4TNhsaddXARgrw6n0nfUr0rIIhwRtSxkYNmVPkHXKNs0QrSM47xDCcbXzRfR0MGO+XiLliDOtmNsSq/2NxVOV/lRYSFtqrtglp2JO2PibkM1YgxOsGeKWDwA/qPc89zcz4/H4kiD/GnFZm7/eqO+v+TDyxKaJn/D2E++C8PjqEdl6BXHKs/Gc6+unBNKg1zfBfciZHVCaCUObIPY/BiA5uwHAmpJgcJWHukAIQ9pMuer5I8ZaOiWIRMFe0bBWAV2pGQUTGu1rTF53mEHI/m5LYTYM65ZWBbRhiGxrpmFJs6wxiWPNiEpVn3og2xzRWYo4IzMlYVKh+uHj82rOOhMIJxg2NQJoA086B+WGNog+jZsOyou46Zwxe2KFsQ1ZnbHtrTqNfBk3nX0aN42hM4bYRaTtDqNnqC5nEQkCVK9BjtECFkIx72ux7Any1dpdxE0HZsww37ILNLHKaHotclC3dKofJrQ1IhwQdB2V0UgckYn4RM8IsZQ2QiZ9B7mpKdHozhHEhq7pO8hfQJC19h32tl0zDsc0jV8rz39WZnEpsfhCfOkWnBBiJIS4+zk//86rOaRLfFX48bvvcTocMjrc8XfrvwbAX/on/5Bm/y6HdxZoLP9g8rvET0sm2zOU0MzDK/xwD+bulON6RVzc5DTcYaVlzwjG6/u0dyy73ZR0sKA4GzLmGgAPtSZPEu6ITzhvrvGcEdfLBW625mF1t4+Y7oixPHM3qYOa6TYADmlNyaBqaeKAK+0J96JrXKs86bQ2Yjafcm99D4DXJr6DfHp6itb6wkXhq4SQApmOMX7XjEEV8bK2tKFgrzlnNRggq4446pCFJWgbnoR+MnggcywDMrlAil7jGwS4lWYkvV55GWlUn6Y3coaizSh7N44qzlC2xa33MUaTBR0b0eKE8Wl68YjZakEeQl5lzM0CJyRn0zmycoRnXiN3g75zEI/YXy2xcsqxVj7tT74MCwkuwkLqcIgtHVfshufskcgVyrRsxiBtyKmbUZ/6wc+rg6s82z0DYDKZsFqtvvLP4RK/GJe1+esJW3a0xzmPm2dsbYhJn/OdZ5ZmmpAH3jHBxBn3RwNuVd7WLVu+SSof8vvuu+wZgRCKaG9BZeBk+9toalZ5hxxd4f3MS8BGzS1e74W7cW8zlqTnXG1bnvfDx4dc5yyuwTnOjcWlmuu7nF27ZFBVlImXX8mmYhJWNGuDSB0lMTu9RbdjNB1xl/uBuyxl6HYESUNYOzYuYd1NvMQCiJsVAEb1KaR9mt5ZaAnqMan2x16KhoIZe33cdNKN6ISgacFpT4qNTUnjniCbGte7PMyqCqumSLtiEQkiAtAhXREhgRdaMsWTbN351zuoxYVjkDRDBuWWPIoIZEytJAIY7HI66R+TtECYodqWygQEfQfZqAqFo7IBIhW0fQe5EiHaQhgZavPlHWQhFFqPaLsl42hMXfk15+cJ8uxSYvEF+DIN8n8DeB/4t4UQ7wgh/lOf+e//86s8sEv8athut7Tnp8wHT5Ch4139HW4sF8zOnkKccSs9pRIB30+/xRu24sq5Yz+6jpCaHx0MudN9gHWKuNznqYY9kTPaKeJ2gd4rOMuH3AxadquUq0wocXw88EXjDp+wKg54EOxxLVqi4oL74ibD+hO+0/tBPuztyo6MoDq/TisNzgbcdc85dAXvDF8nrDqUM7hQIYS4IMif7SDv7+8j5auRWsrBhMDktDolqxVFb4YpooqDcoFRikqCig1up8iagidRn6Yncgq7x0ieo5nhBFSBgo1CZefM6p9O05vRUbYJMvTnp+jDQvQ6whhNHDQ0FrpwxUxpjFRMz31YSGtgr/SF+mwyQ1hB/MK3X25K361eBQMOz09p9CFPpCIWObq//M+UY9QvGlUcIcqGI7vhuZsRZTXD3ZL1EKSJWDKmO38AwLXBNZ7nzzHWMJ1OWa1WfE5D8xKvAJe1+euL+uEG5xwlFc9JMOEJt586dsM98v76Oz68Ticlb6oPcLsJe+0RN9QD/qG4y5GRGNExHbY0heOsvcs8eMB4kyF0zIfDUxwhkXuNuzvLmd4wbHuf4cGGQ13yrHew2Ldv8DBTBIWhA1ymubWtKM2OuG7YZRNwjsiWBNLS5goz9fZn6+hTD2TVNiRtR5GmTKJzpHIkjeXUjtm4mG3mu7BJ53e0QlODiEj7XcbzUBA0EzLZE2RqWjVlzpZKGKLONwPKTiADQyhyOpORxb5O6q7C9cNy07rGqhnYM5aBIHUx6JC2VL2kBWJnkYEhrks6UTFrNa4nyK4bElcbdkmKlgGVb3Yz2G1ppf98XiscNoxRTUNpAgIriExEo2pPkF2AzQKcEISmpVEhyiji0PohPYD89Au/J0EwpW08QbbGk+nPlVh8iSPG1xlfxiz+Z8DvOue+C/zrwP9VCPEv9/8nXuWBXeJXw/d+/GcAvBX9E563V8gHE/7avZ8AsCiXTFTOH49/izZ3jMKH6DrnKL3Dk9CwiAbMq/f4xvo6yoY8JeRAbNk/W9FcBaksT+qAqzs4i+Z8C81z2fJiVBPYhmv5M5om5dxm3DnyvrmPkqtE7T1+t+kwTnCvLxRXIsPu2HddF3rCN9IFY9Xy/uA18loztC3ByFeYe6t77CV7fiqXTwnyq4IaTfo0vSFJ7dj8VNy0vxnYRQFSQVIpRs2W49QPuYzsjsfuDhN5hpRDBIJGK8RWYAcr9vqwkKCvS3MLjUmJwr7AJ/2CVJRYo4iiAtFFdPGKce8oMTtfsk0kOMFB6QvfcjjGSEl45ov9UXCOE9DIkL3zc6rwiEcqQOI4rJ6hbMRSV0wC/36KWCKc43Z9SoeGUDPerFgloLqYHRlq8wiAa8NrdLbjRfGCyWRC13XsdrtX9nlc4qdwWZu/pmjur1nJEqHgabDj5qkjrAUvJntExYpOaZYzv6v3reGf4Ta3WKsTZmLL++4md5uGdfQBV0LLYNex7m6wrz9hVkwAeJB+glWHlPHBhYMFrUB0LbU2zKOCk3aEUI4RV3lnOOBw4W/sXaq5viqR1qKNYT2eEHQNWVhjTIJtJXbs69ciPqfuvAeyamuSxhPkcepv6kdNy8IO2aiQPPM7a7rx/5fWJU4mZLknyKtYoeoRmdwhxKdx0wNn2UlBZH3jYmMFIupI5JrWZgxVQRMEhE0Bre9Gz5oOqyZYTliGkqGLsUpjan9ZVQPhrTZjS1RXVLpm3EagJVqAMSlRs2WbDhAqoO7lINlu6xtBwLiW2DBCthW11b6DbGJqVaOw1CiaXt4X9ruMwobEgaWyGov4UoIchnOadsEoHCGt3439XImFs1BfyuM+D19GkJVz7jmAc+6PgL8K/M+FEP8T4LJV9OcY3/vhj1hkGfuHZ/x7xb8EwF//R3+MHV2jfm3F2OX8/vz3sE9r0tZrlQ/j23w/9RfKtvqIN1bfBuCZhgO5Y3Z+yvYbvrh93Bqm5yG76QGvI8nbluO9iFvdQ8x5ijCOnQl4be8huRlwlmW03TFvVx1POeI4e0pWKibTlm7tydnj7Cq3x/6OfhWMecGMyITMegeL++v7FwN6VVWx2WxeLUGezIjLBU0wIqlbzjp/uah4w7hP09skEdZA2mlGzYoXL+Om3ZbHXGWszi7CQpwQyBJM6AnyaSS8nyYwcwLXDRnIp7RSUfZpelGzwlhNFJZom7KLThjiyXO22bIe+OK7l/tjy6OEMkmQjfRhIdEGem1cuiswwT7Pequ3m8V9NFN24Zph+DIsxP95vfA3NpaIyWbFIgpQJqUTAaI4g67h2sAvwk92T5hMJgCXMotfHy5r89cU9YMNHyR+W7yKH/H2Y/9xP7h6yGC7pMnGbEdz5rs1e+kCt71J4Xxz5Li7zlUjMLPvEQjYW6YYFxMHz5mJCc5ZHoc/QjBkmyXczh2Po+cUdMi6ZNcq5lHBtojRQ5BC8r3pEaP1pxZvg9qQNB0CWE+GiKZiHDS0te86m5GvbXmwo2znDGVFZCsiAVYphrFfg6ZdxcoO2aqIPPU1j/YcaR1JW2N0dpGmt4lDVO0bJ0FQ9XHTIakVrJUktN63fe1ApYZUrmjcEC0sTRQS1oWva8Csdlg1wnDKIhJkLsIqSdv0qXa93EPHlqBs2OmOqHeuiJSgMQlBu2GTDZAqpO7r7aDY4IQDITmzIXUYIEyLtJbQdoQmopI1AoNDsnJDQuXQLz94ExH2oU6l0L9EB3lG25wzjsYIWyCB818YFnIps/g8fBlB3n5W49YX5L8C/EvAt17hcV3iV8BiscCcnjCZPkNFjh/q3+Vws+PG+z+gmV7htb6r+/+Z/R6Dk4qD5ZZYZkyiA/7wQDByKx5Wzxnkd9mpko1w7FMzWT6ieEvRthHnwRqeTxhEr6ER5KXm/uGU2/pj1rsDmgpub16gJjkf734XZY6xtuN2XfNM3OE0e8RsHZLMatguCTrDJ8MbjN0TAGRnyMlwzYQ3v3mEc4776/sX8oqzM1/MXilBfhk3Hfm46SdtHzcdbxj18c7Ll3HTRjHqFpwO9rAI9tslj9Q+Q3mO+EzctGwsXbRmv7acxoKhkhjZMrYS243J7DN2UUKe+bIY1WtsFxKEJYMu4Vn8nLRPsNJly2roHxdXE2JXsosiyjTBBAqTj4iSDS7up6uLBqNmPNf+d97cPMDIGbtoRaj9MebaF+CD0n9HjMsYb1fkOsY5v0iteyeL6wNvI/V09/SCIC+XlwMfvyZc1uavIVxraJ5sedA8prSadvCE7z6xtEPNajQg2WwQYcyD8Ywb208AiJevofiQZ3ZKY4ckLkHse7lasLgJwJacaHCFU5fTsiToAoJQEjpYi4JcGXRbIrcdmW6pt5ogi7BixzujPfSuQyiYdDnGGLLaE+btKMLVNXtBTltEtDqgCjMc3gO5afcYCO+BrANfl0Tod78mTc3aZOx0QhdmtApcvfJyhK6lCxPS3HdGi3SAvYibLtlRM0HQuoSthsh6IrhyEjJDLNfUZoRB0MWaqCnQfTrdtJE4mdHxglUgfJqeELTG10aV9DuJoUEWhnXocG5M2JWoQFDaEGU21GFEFQU0PUFOCj/87rTGdZpd3HeIO0voKiIbUMkaKTwRXzQjEt0h+/tdaxKkBBlacqcgP/vC74rvIPcEGcdIuc+XWMDloN4vwJcR5P8hP7Nd55zbAv8C8N97VQd1iV8N/8Effx+At7N/xOPmOtvBjL/x6B1wBletuRoseC+9w6mbc1fm7C0bDpNbOOBPrk55s3uHxkJcHPE0rMlUw6gJGW0fYW+0rLcz9rMtxYuMGVcA+CRWlFHMa+ITzrqrPJBzbpbnMF9xr/oGunnAvjEMXcexfY11smC+CVHxENNsGFYNT0cHXK0/YiNSruT9hHZzxDe/c5OT4oRtu+XuxHOCV+lg8RL6YI+4qqjDjLTaceokINDRhsFLgjwaU1eKIYrUnmHCgI0Ys98ueBzNvFG9yD7zrI5OrtivHYtQEAUprc4ZGgU2QlULdnFCHVuMDIjqFaZNEALmQvNMnaNdzMS0mBbOxr1PZ+3DQsok6sNCBG6bEqSfCQupLFbPed4X7G9uzmjDPXahH94DqIQvoIPaF/PKjRltffEsQv8+loxh9ZAr2RUE4qcI8mUH+deGy9r8NUT9aIszli0Fz12GiZ7x5hNHOZ6TO4cANrN9zuOQO/YDXKeZb99grO7x7/NdDoxECEm4t6I1cLzyA3qL0iLHN3g/8Tt4w2afm71Nm7AKKwWx3rGX1xRS0W41aTSiUy+wUtGUHS7VTPMNja0Y9t3W3TBFtjWH4YZmKykizVpOMIATDtvMiY1D1BVW+1pWRx22FmjjyN2AVgaEZsh6ANQ5oVVEpqOJUoK2Jq5b8iTDXMRNN+Qv46bdCCFL0pdx01bAACK1orRjShJMrImrCtnkVHRMOo2TMbV6wTKApA8LaZzFOejnqAm0gdJxHoJxU5J2C6H05LX3R97GCa2SWLiItNaBojGaKvFrSNgZIlugkLSyQ+DP3aYakeoa95Igd35QUseGjVWwe/GF35UwmNM0C0aBf+8D2X2+xAIuCfIvwJfZvP3IOffx5/y8dc797Vd3WJf4Z4W1lvd/+EOWk4j9vXP+b8XfBOf4F//+H+KiIauDc1Jq/sO9/xwcFwzVOwjbcJjc5uOwYhkNuVb9mJv5AWE34KEMOGTDfFEjkpZgWHBcpNw2jl2XcYsBx9LyZPgyQe8Ttvkej9Wca4MFMqz5RNxmVH3Et1uvU3skxiDgoNR09RUaauLaMJFb9rsV76W3udoPnVkXMxgO+Gjp41LfnL4JeIKslLogZq8CwcE+cV1RxylhV9FWGuksKt4QVwppLcvhmE0zZCQEifUFay2mHNbnnIYpqVr+VAe51gqZt8zqGicEdTLFyC1Jn6bXlS27KMGomjoakZSndIXfOpwLxXPlbxzeMDtKG3E+jPuwkN7qLYoo0gSERawCdLqkl7JRmACrJlRSsVOS1+oNVXRAGW5ZB3uAw7qKOhxjq5Cp3bJlyrgnyJv4MwR5+ZBABRxlRzzdPiUMQ7IsuyTIvya8qtoshJgIIf6OEOJ9IcR7Qoj/zK92pJf4KtHcX7MVFULBk7DkYG3IdoLz0T6uLrBCcHLgbdvejt6B9RVCAl6TD/jH8g5XOqhVycGgoykcp+3rzIMHxKsAmc54d+jry6h+nbs7i8WR9A4W6eCMq23DM5EBggNxxCbydXrZGsww5GizZdeuGFUtndQ0YYhsKmZhQb3saGPHOVMa0SKtxnVDUtvR1oamDyNqIovL+zQ658ld3IxZpeDKmthpAttRxhnCtiRN4+Omy95FImov4qZXNiNSW7QNCVt1kaanogW1G7J1GfRx00YGrGXNxMQ+Dlt27CQkvAwLkZhakmlH5wSx7nC15IUEx4Bxs8JEkhUCiz8v28h3n+sgIGx9Vz0IAoouoBr4m5HYQNDHTSMcgfQkdluPiHSNM/6gu8afH5W2bO2XSyzCcA5YBqofcBTt57tYwKXE4hfgl42a/u++4uO4xFeEf/zOuwRlzlvzP8EpyU+S3+GN8yVH7/0p7fwON+6eI3H8/uz3MA8rJvkHCARX07v80cDf9eblO3zr/HcAeCQVR3LL3umC/E2JEHCvVhysFSfjPb6N4sw1vJh0pF3B1c0xbZtwajNuXfUeuQ+zq8TNh/ylusU6+Fj0OtfAsHt6EyugEilviWccyZIfjt9Glh2Ra7Gxv7g/WnmC/PrkdcAT5L29PVRvwv4qoI/2iaqaKu4tjhYKaR1BvMK4jEHbshqOWVdjpsoijd/yWsgpB+2CVRQTiAak5eWMcB2oPk3P31Dk0RQpN+ieIFdFSB4lIDqqaObT9DZ+8G8qBc/6aNPbrmKtUqySVLKl6MNCdmFKGacIZ9ELg463zI3vXDzP5kx2OUqknAaKq21BG/oO/MNgRCAtUFHGM9pCc8UsOBcz0t5IfjkIwAnOmcDqIeCdLJ7ungKXVm+/CbyC2vy/A/5D59w3gN8G3vuKn/8SvwKqT1Z82OuPy+gx33jia+mjg30GuwXlYEw12ifoOt6YfITd3mGhPiISLR/ZW7zeNKyjn3AttIx2LevuBgfBJ8z6xM6PBw+xcg8X3uLu1vA8OCdrQnAONdxxpCqeWX/DfsW+zuPUIlrD2jlsprmVb9m2CwZVRZEMQQhEUzMJK+rzGlLHhiGFLoiaCSAZ2gLZWfJ4QGRqXAzKqywoeovMtBqxygS2NKREBM6wSf3/xXVDng7pN72QcUMt24u46YH05yurQ3Z9mh6Rr6Nru4+MIGoabJCwFR2TboBwOU4kFDgvsQCcCmjzgJGC3GmSPm76FE9ur5cb2lixxqH6NW6rHAJJozWq8+RUBhGFCSlTT6JTq1DGP4dCEOPf/LYZEEUdTevrd114CYnIWrYm+FKJRRB48pv0u4IRJWe/UGJxSZA/D7+MD/L/Avjnfw3HcomvAP/vf/AH5GHIrck7/H/zv0oXR/wrH/0QTI1sV9yIz7kfX+Xd6C63upYbpy170TUilfKH1xQH7pj36hXT3VvsdMFSOo7kjtniKZvvRFgr+YSS+HgAwzvMkLSV48HhgLv2I+rlCNF0iNZwc/6EbTdlkaW03XO+XbU854Cn2QlxLZlPGqqFLz4n0QHfGG8JhOXD7DbrLiY1jmjq258fLT/iMD1kHHnP41ftYAEQXj8kriqq2Bem8VojjUNFa2o3YthVLEdjtuWUUdQiWl90T+WEg3rhuweAVDusDPs0PY0900w6P4iSR2M0W4RV4GCXj9lFCQgokilhs6ZZe63vLDCcKL8KXBWG83Dch4VY1uWUPU7ZBRnbNEM2lvDcdyyuG1/8TgYzDpbnIGc8DxQzscVoT76fqujCC7mKxpgCjuyGY+aEcoUyDduJQJqQE7f/U1ZvT3ZeNz6dTi81yL9GfNW1WQgxBv454P8E4JxrnHOrr+r5L/GrwdaG5tGWT5pH1E5RD57w3ccOk0ieH8wZrBaIKOV4tMf19TNC1aHWN2nsOzgHp+0NDo3Czv+IQMD+IsO4mEQ/Zeb8Vvv9+M9wcs4unfH61vAgfkJnHKKtKZWPmH7ejUA4JvYO740S5i8dLDLNa6uS2haetA4m3uLNFUTK0O4UcuhoRcAmXBM0ExSGpNuRtB35IGPkdqjEoWtLi6IVfvgtKVPWGdjCkZEQOsNq2MdNNzV5MqBqG1yXIJOaSjTMEJzbjGEfNz0so4s0PRP4Orr9qbhpxY6OaTdCmjVWzihpCV8SZK3ptkMyCVs0A+mJ61r4un+92lEnGgcI/CDiVhpildIEAaq3UhNBQt4F1OkKgNRKpPGkODIRSe/lvGmGRFFL2TaorqPO/Toks46tCaHNocl/4ffFd5DBmQ3DYIi0u5/vIMdjQFxKLH4BvswH+W8BbwP/2q/ncC7xq+BP7t0nOD3h6OgT4qzl37X/deLK8Ff+/p/igpTyxhkhDf/24X8RfVpwXX5EVNdcy96kcR0/ODzgzfYnNFaQFFd4HJbEsmXaBEyXH9G+bthu50yGZ1RPxkzULQBOjebx/ow3gvdZlkdsmoi7m2PEpOSj3V9EdS8wtuVuVfNAvM5Z+pDZJiTbq7HLdR8xfYOrmb9ISxHxgj2CLmH/pifEHy0/4o3pGwA0TcNqtXrlBFnvj4lbSxn7Arm3DaBzqHhHYScMXc5iNKUrY0bhDtl7cj5XM/bbBVXvHhHJDWhf6OtAYRcBE+eL9i4YIFyJQJA6x7YeXoSFlOmIoCsxq0OslQx1x1L4xehAORbxkL3FGXkIRZ2yb85wQnIy30e2gvDMF/A7tk9RisZcWZzSqQMeKU0mdjj8wN8L5Rhr7yZSxgmibLhuVzx2BySDmuFuxWbkUCZmyZj2zA/5XBte47Q4pTY1k8mE9XqNvfTUfOV4RbX5DnAK/JtCiB8IIf6PQvyUgP7la/8PhBB/IoT4k5ezAJd49ajvr3v9cc6xzTDxU95+6iinUyoHylhMMuCT0YBbpQ8IGaxeJxQf8wN3B2FiIpGiDr1NozjrB/REQZIesjUFuXiAtBHrYcj10vEseMFOtKiqZFsL5lHOpkzQA4eWIX842WO+7ElXKjlalQjrvMXbqLd40w3GxJha4qa+ti3jM0w7ZaxzVNOQNC27bMBEL1CBI2o7NmKAUr6G6jJilYEsIHMxUdeyHvjaNSh3fdx0garH6NDHTY8cnJsBU+G/o8Mq9hpkwAa+Y1vaCUHsj18ISemMJ8h2g1FzVNdQBQE4cDqg3WRE0rEWipF8GTiyAuB6WdH2g3fK+MtmpxyRSmm1QgDSgNUZRRfSRSsQktQCra+9oQ0J9BqJZdsO0HFHpSRh01AUnnSrrGXX9kLoL+gih6FvfjTtOfNkDmbFujO09jMmN1J5knwpsfhcfFkH+W8C/0vn3OWK9/8H+Nv//v+LRim+MfvHvFN9i+XokP/y048JH/8IM73J7ddOkcC/ffA3aO9XTKofA3AtfZ0f6BeUKuFq8X1u7q4QdCkPZcxVsWGyhkBuCWYFx7sRt2kpdzHXmLMTjvdGAislb/Ah59U1PgyPuFP7BL171Zvo5gE3uo6BMzxzb7NMT5mvQ4JBiCvPGVQNH05vcth+QItiXOc0hNh2j2/91jVa23Jvfe+CIP86HCwAZBYQ6IyqL3rTPMUZkLqjEjHTbs1yNIFSMAs2BBtPkJ8FMwJnvH7MBaRyiRBeS1drhVtphvoE4RyLWKN6c/8pLUWXoUNfeIvEF1m1Tui6gCSsfVhIsGWmNU5I5qdLdrGgM3BQ+k7Gycyfl/jEdxduilMcsNYZh6cvqKLrPJAaRcdee4Z0Aee6YtpPj+exQjjH3eqEmpAu0ow3S1YpqC4lJ0Wu/CJ7fXAdh+PZ7hmTyQRrLZv+PFzileJV1GYN/AXgf++c+x0gB/6nP/sg59zfcs79RefcX3zV1+AlPkX90ZK1qkALHoQlw7Jheg7L4T5N42vG8YEPCHlDvY8rRhzU1zlS9/kPxG9xaCQORzrfUHXwbPvbKGpeFA45vsmHYYnAkdUJE/x2fyFqKmUJbInedqS6o95p9CDEUvInkyvEW08wR65EdpA27acWb23FOKzoGt+pdCNP7LbhhrLdY6wKQlsRNx1FljJL/RzHsGnYqTG2J8jU4adx022NBOq+AZFV20/jppsRcVhghMUIy44x+9LHTQ8+Ezdtew1HZwfEkW86SGGprGVshuhujdVzdJeziJSPm1YBXZ6iBZxLxUz2soieIF+rOlzUE3o7QHcdO+X6uGmFA4LGYFRCbTVS7hBhRmQsttcnxyZG6pwEw65L0amh0YqorinqAGkcMumoWk+Wv0iHHPQd5KY5ZxbP6BpPghc/20VOZ5cSi1+ALyPI/xXg//55caaX+POF/8N/9B8zXpxy8+r7xKOGf6P+76M6y7/2D78PtkOL+0yCnD8ZfpNjuc+0NFw72zIO9hkEU/7eNYV2Lc+Ld/nOuQ/leiwUR3LD4ckZ5V2JkI57teJwpTiN5/w2AY9Ey9nYE7HXug/ZbuccuyE3918gdcvH6jbj6gN+u5/gfehmOOnYzwO65iqNLRiWDS5y7NXHfBxd563cF8mm3eOtt6/zaPOI1ra8MfEE+dfhYAEgQ4WMR7ShL6qDOqLp0/TqULLXvoybbkmjGpE7oqbicfwybrqgdDOGaoEWE5yAMgxwaw3ZGbPGeyGrfnBkH0vdDojD3roo89rncFthrSKOC0QX00VLJsIvNOPzJdvUh4Vc6b2Zz8dTHxZy7gv/NNiAFjghGa23tMEhz3qrtxvFRwR2ziZaMHrphRx5znWz9DHSrYiZbFacRxrdZTghqdsGqg3Xh17+8WT7hOnUb9Neyix+LXgVtfkJ8MQ594f9v/8OnjBf4s8Bqo9X/Dj0ev8iuc+3Hn6qP87yc8pkwHZ2FYDvDH6M29xipbfcksf8Ma9xs7Xk4YqrqcHtLKft6+wFD1DLCDk84p2hrzvj+jZvbfsuo9EgBEmwYb6rqaSkWXsHC6OOqXWELTtEIplVOZ1tGdSegG3GCa6umQcFTZFgpKJJfU3LdU7ZHDKSJZGpiKTAKsUo8rVj1jY04ZxGOUJT0TUR634vI+njprveIDj7TNx0WI9J1Kdx07mYfho33Y6ogc6AU3496mxKHPcE2Ta0rUEhmVYlRs+QZs1pLIjROB3S7kIUcKwkB+JlCp9vCBzVFsLeUrObMCy27LQiUqkPiQKSoqKTvnaHbYMIBwSdoWoFOC+xcDonxLDrElRqqANFXFXkLiDoHDoxtNXLDvIXEGQ9AaBtFuwlezSNX1c/18nisoP8ufgyF4u/B/w3gX/r13I0l/inhnOO/8cf/Hu8+6c/oA0Fd4/+kO8Xv8vx5CZ/4+FTxu/9EDM8IvsLW0LX8W9e+5eJnm55m/dIqpZbg29ineEPbk952/2EDzrDZPsWq2DLSjo/oHf2kPV3IpwTfGQq5ElGO73JDRR53fF8JrlRPyI8l2AEKxPzxnW/Bf9wcIWk/ZC/1LTUTnFfeDZ4TVmKZ69hpKV1MW/zmCOX86PRW0wLf3fv0IRh+HMOFi9evEBKyWw2e+XnVwzGBKai1SlprSjb/udRzX59Th2GdM4iQ0dUKEbNjmex39oakPPU3WYiT1GMEAjqizS9BfuVT9Prh4yZW7DdkJF6RiP1hTl+XK+wVhNFOYHJWCfHDIT/v8FPhYUECGfZxQlFmuKcxtQpSbzBRf4xYV5j9f4FQf7G8j5W7bGNFhdeyEXP2K+UfsiysSMmmyWFTjDCL3BLJrD4hJtDv037aPuI+dx3LM7Pz1/JZ3GJT/EqarNz7hh4LIR4q//RXwfe/aqe/xL/7DCbmu6k4FH9hK0NaYYP+csPHSYSPD06ZLQ8x6ZDzsZ7HK3OmA2WdJv/H3v/HW3beZf34p939jlXb7ueXnXUjqpVXOSOIRgDdnIdQgkwQvolkIR7fyG/ELhASCE3BAgJLQECCThxjDHGuBfJsqx+dI6OdHrbZe3V2+zzfe8fc50j2ZYtByw5kfczxh5DR3utud8111rf+Z3P+3yfZycTmSeqXkx3czCJGLuPsGgompPkWoJec1xECI3TpTWUcLA5wKFJRigSinMHC7fcZSVJ2NAKKKnR0paYWXljOo5SsqJJbTIkynwqUX6DPSl7aHHEojkhnuiEtsnIqCGBUA9J4iZFlaDHIfrcakfYedPZDBNEcTdKQEXOmGUew6tx03Mm1MgSQKdwNW7aFhhRleLz4qZjUacpxnncdFYHBH4iEGaKIQIyWaBgX210I2SaSx2aUYw06qB69Kx53LRpkwQGQsCWpVGUKZqV4UZTMhHTSvRrDLJISxSCMb7tYGgWwbyZL02mJFr+OgqxhrIKGGlKkFkYKmeQpR5gIfGlA0VJqmk4UYQvbPQMLCcjDV+cQdY0A9OsXZNY+FFez7/EC9mtb2uQvwxedEhPKXUceOfLsJZtvAjWp+v8ztO/w4/f/+P8zY/+Tf7yH/4f/NV/9i7ec2yLejDlzTvfC67gP6i/hR1KfviRY8jRZRxzykqlT8es8kfN+wiuJLT83Ct5d/F6zsSX2XQbXO8/jJZZuLNFzjthrj9ODOqD08SHJdNpjUKpS3KpRt3J3SSmocmZ5Rr7jWcZjRdIAtg72qRUG9IO9jJ2beJkjRuDhIvsYMu7gploLFZiplu5LnfTWeDmco+ilvJU+TBhqPBkjCjmH89Tg1PoQr8WEtJut2m1Wi+pg8VV6KUabtAntsp4EdfipnV7Qm2aN/JTKy+ahdigHI1oz+Omq2rCZbWTqtaFudVbpmuIGaTOgNa1ND2JQlGXGjKt4qXrTB2XaTG/aDhhH5maWFZIKbPZtDcozMNC9CBlWM4fp8UL1OkxcVxmBQ9pachJCcsdXQsLEWFGZixcCwu5cbxFZC8wcfpk+nNeyApBIfIxVEpAjdoob3rHTv6eDahA9wx1p07JLHFhdIFyuYxhGNsN8suEl6g2/13gd4UQx4BbgJ/9Gh9/G38GhKeGSCSBkXIJh9Ta5IaLkqDZIFAyd0hwPZ6t1tgzzu9p3MFedHWcoXQZpQvUpAutx9EEtHr5gJ5tbtKa15Jz3tNIbYnQWeLwOOOcfRk7NkBmqFLIshFyWeYzIavqEOteBlLRlRJZNFmZTJgkA8pBRGxYJJaFFgXU7YBomBHZ0KFBIjIEGiqp4WYSFYZkRn7DHzopMhYYqcJYOAJAVU4ZazbTQl7DzCSX2BXjEKV7FPx53LRt5BILLUDTUgIRoxllKipkqgmsedz0NANhZXhX46ZNP99xS3zkPG66GaZIvY5SW/RsjbJ0UYZJOreS8wsCTeWexG4YEOoh1cQCXaALyLICTjRh6npomklk5M8rTiekWn4D4UY6mWmjJzGz1MKWCifN46YNJL60UKWcwbfTBN9wMaSGZWdE6YszyACm2SCOezScBkE4b5C3JRZfNb4qmzel1PpLvZBtfHkEScBPv/+n+Ylf+QmefO+TaB/JWH2/ZPkTTdZW/hLXd9Y41HoCuTLl3w3/FrNile86dYHCySdRpkfhaBsdye8sfxvFaUIrCNjRmdGyd+IZZT61km+nWdNHOdq7CV2ZnMFjVYyojgSmmGC0ZmxOqhzQYtKpxRKLTFGc9TSmrssh7Vk60Q7OaC32z7pk9RknJ3ehpxsImbInjrjIYbaK52gNLbxWBMMBKMXZ4h721/K7/rbVYEtWcTONwkLejJ0enGZPeQ+WnheFzc1NlpaWXpZzr1frOH6f2CrhxgmdZK4xc8aUg/lW4jxu2k11ykmfdmFuy5ZNWKNFWet/gReyHklSe0AzknRsQcm0SPWQspyHhcR9prZLaqUkhosdDUiT/Fy0hMm60cGSJWrpjDTR6FZyNiHzl2ixxcx1mJU8MBRq5GAW+xhzwiGOQepVJppOqAn2hxNCu0Vk+PSt3AtZqYDIrhCHLquyy5AmlfHcwq5QAAV9KtA7jRCC3eXdXBxfvMbq9/vbxfblwte6Niulnpjri29WSn27UmqbWvpfAMHTPS46I4QmWLP7LA4VpaGgV1oguqY/3klo6BzmaVRisji+nqpxmvdzO1WpoQsbYyH/uIS9fQAMCPG8JUIZ09NOAAWGRY9DE8lZ5zJhlqFFIVPNoGHNWE8qIBQ1uY9TJYvyKCYDZMFg32TKNB1QDAJ8L2+ktTikagVEXR/pKQZUCfQQOy4DOiUi4jAlsj2EUiSOQk1yOYK+lO8YllXAWLeYFeY2Z0kPoRRuHCIN73lx0ybaF8dN6ybuPG7algsAjJRAc1NcbUgiS7haTOTYWLGPCvI614gVUq+S0qFnCwo4ZLpGEufXyji/p0C353HTZoqTPT9u2sGMx4y9IkI3r8VNF2YTEi2b65F1EttGi0MypWHLDDvziPQIHUmEgW85aAIsmSE1HaEsbEuSKp1E6DB9cS/kJM4ZZE3mEpruC3kh+9tf8xfCV+uDvFcI8a+FEO8VQrz/6s9LvbhtwNZwi5/4xZ8gfSxldbJEYcvnijT5yB338chdb+Xei8+wr3KSpYNP8UBwLw9WXs+BKyE/cGKLrP0Ubj2jtThhprn8+o53kp2bcHP8WQyp2Fu6CZmGfPi6JnvVGR6Ipuwb3E4iEq5oGqv6iMXNHv51GpqmOB2YLA0Munadm7A4r6ds1HIW9QhPM54scEFvssProxWnnMoO4oTPcjiOMVC05SEGhQ7NoY1d0VF+n2KYcKq2i1p8FonATiN61NCSKvsO5wXt9PD0NXnFbDZjOp2yuLj4spx/vV7HC2dEVhE3DLmS5l8Z3RlT9vNCMyyVyUKNAgaltIPvFQlwWIh7XLKaFLQezzcD0GRGag5ZDBUDW8M0y2TGFC/Li2jiJ0wdl0yPiexKHhYyyy84TU2wbuTFbF82YyoceiUbhSKeNWjSYeJ4+G4BQYbeE5iFLmWVr3XLq1EIAwytTMfUWU19Eis/zxeMMraeARGB0yCeGuyQfTZYwEryQjyoaghlsKYWyTq59GV3ZTcXxhcAqNfr2wzyy4jt2vzKh0oyotMDjsenkAri0lluvZA3audWlilOe8yKFYJaThrcXHgSNdqFEDoHtXN8XBxiNdPIREalFhJEsBbkA3rtQKDX9nDa8BHEuLGO5ugUMuiYA6Z6ih75TGaCpu0z9h2MMhiayeerdRb6ueZMFUz2DkIymWDHMeNyDaEklgpw9ZRkrKGVJCE2Y3OMmVQBRSmZYKWSmVegKH2kB/o8M8NeyWdOSipkojvElkeqg4qHmNk8btr08KbPxU2r58VNz4ioIVDSZmwI7CxnkIdKIIoSVxsRyhIZGoltYkc+YpbXrkYkkHqJRGvTtQXetbjpfG3atbhpiR6kjCyJVBXsa3HTNno2YVwsoXT9WoPs+ZM8/1LX0WOD0DYhDkApLBnhZE4eN41EIWjHdVxTYl51Bso8LFMBipn4KsJCzDpx0qfhNBByiuAFJBbFFsQTiP3/mY/lNwS+qgYZeB9wAfhF4Oef97ONlxCj6Yh/88u/wMIxk+PDKg/JFR6u3shlfRfe2Qm3P/0wdy59hB03PsLn0rv4FevvUZlm/PSzp1HPfhwMk9Yd6+hIfn3HO5lRINzK2N0/haWV2FU4wrngHOeLK9wV3M9EaBSnO7ns9kmFYpUJC+0zjG63yDKdS2JGvFkiqO9lJzpBlLLRVDTjDvXRkDSy6cgCe/flDgenvF00whO8KswZjjOighKKpamBTFaJ5YxSmA/oVcN1LpmL3DC+AgiSaIVX3b2faTxlbbp2zcGi3W4DvGwNstFoYIcRkV3AjaZsoqGUwHDGFIO8aA3KVeLIoCh0PLkFmmCk1VmI+7SdEgV9gNC8a8eMDR1tmlGfF6TQa4IYY83DQgLfyr2QtZTAaeCEfeJx3sTWDMW6ljMme0TEwCghUAR6wthv0KLDxCww8YqIRGF1UjQjZmc0d9goNVnqd1FanQ1Dpy6mSH3uhaw5FObDK75TRc4ydqgxl1jA9AKKswHDqkLLbDrUSbdOAbC7vJuN2QZhGtJoNOj3+9tWby8f3sd2bX5FIzwzRCWSDiM2ZZGkcJ67LknSok67Ucv1x26JTnWR1njAUn2LbLyXjngKS2Q8o3ZzME4YWWfZbUvMaUYnOcCCeQ67b6KVV3mylNeHarjM3nldS6Qi1cHRApxhjGOkhCMTs+ggiXiotgNvnDdbjplQChVWJtGVYlCtYyYhJSsmy1yyWIN63mQOnC4qrlHSA8w0pBDlFm8VNcbwJEYoSYXAa+0BoECCrztYqsi4AIQzbKVjZQmx5WEkUe677BZJg1xuZtgxs7kX8pgySotwnx83XVDYYkQoK0zx8rjpKMCIZvgioZ6YKOGSsE7PErgq34JLUCgJxnxw2zIy8BV9UyBVFS8Zo8w8blrIMTM3t3i76mLhBflAu2HqJKlJ4IBAYWYSSwbY0iDUYoSWd+LdsIZnJGhzsxqZFtA00J2MqdRfXGJhzSUWbgOBoqxLOl/SIM93Y6ebf4ZP5ysbxlf5uFAp9W9f0pVs4wuQpin/4V/+ey5v1HlgqcJbtae53XkGozJEL03RCxFpKWXDWuLXgh/h886rKU9T/vFnr7CnGxC0n6J1dIJVzugZVX5lx7tpXuhzMHyaYijZV74eXTP44AEXoSSLo8+wPF3BiSuccyVNLaAUF2gMTrF2OGM8atEqdcjO7aKxOmdzA4NnVoocFQ8xHTbJQsXKrMvigU2CtEi7XGPn5mnuiWK6WZErZq7v2mVLJmv7SbVTJHI+oJdN+HD9taz4U7ZoIpVLpVbk0XaulT5cz+eGNjfzL/HLJbEwFpo4YUjgeFhplA9pqBjdHlMI5tHL5QrDaZmypmHJvIEfiBqLcY+B5WKLKUrYcwN5CE2DQlenHo+BGlO7jiGeQcg9QMbEr5I28+GYwK1RH5wi7u9AKagaGZsql6Osail/6jaojwbMTMkoqNKUWyhdY7O1gBYorK2IANivtjjOXjpOjV2dNieWl7mgm9wmRijyv7Wlwy1WQD8uEHgWWjthT9JjYhXQPaiO+vRLixhpgalRRBucA6XYU94DPDeoJ6VkOBy+LEOU29iuza90hE/36RkzpKFzVotR2pSDFxXTRotASspSImyXk9UaRzYfgRI4/X0gnySVGt14F6spjKqfo2ooWsOEc8lOdnsfJJ56CE3n6fJllLDx5BEOTSQSSSH2CIFCsUehHzMr6iQTk/JCBSU2GFk3oaYdhCWoxzNUJimEuSPEsFZAhAFVKySJ8t2vrJY3mQOnRzjaSVWfoichXpywVSyw6p5G08CJUwKrgOflpIInslyHG5cZFaARhjjKwJIpoeNR7Ce4ccLMK5L6c0cKOyEgpo7GUBaw9AmGquVx01KADobTIwxLjFUR5QicYYShmwxERD11AAEiYGSQM8jMw0IinaKpiJWGYySoWGNLy5A0qMRXGNtNRgjq87jpqZnriCPDwIrz9ZmWhZ+aGMWckHAygS1nCJpIodDJG+RhUGdFb4PMNR1JnF9zTC9lLPUXTdOzrAZpOqQ+D9gqaQntOPnCB5XmZNOkDfV9/3Mfzlc4vloG+ReEED8hhLhHCHHb1Z+XdGXf4Pgv/+F3+VRU4V2t+/mY/WP8uPUbvC19gDf3TmAPqvyy/qN8n/lf+Pvil/m8+2quuzDj//lkl9emHsHjv01lf0TjSO5c8VN7/zq+cOldjDk0fBAhHA5UbiXsn+ZPr1vmOp7m43HAHe3Xo5CcUg47tAGtrRBRiTDLAZenJfYGEhmb7GWBvlCcKeqMCx5HjBNs+bs4LxpcP1qHSsCzk3uRRARJnxuCiNPiEFvFcxRnBs1mhN/Ov+htp8XN3gYlLeHR6o2kfh4xndn5HfrTvXzg5PrG9fnj222KxSKFwpfkF7wkMJcWviBNzx3q6FJiOgOU9CjEMYNSmV5Qo27Ia6bxHa1GK+4zsU2EAN0IkJqRp+mZOtmWRU3mWt2ZVUZnilA6hpJMwgqRmbPJvltClwkMG2SZScmKGV4NCzEEU8tjodtl6giiTLA4n+hu15sIBO5Gzljs1bZQwMAssrq5QeDs4LxhYJDQiDfRpcPAnFCz8mNP5ud/39zqTWkO9WGfrmtgJEWk0AkzYLJxrUG+OL54zcliW4f8smG7Nr+CoTJFcLLHYyrfrRkXz3D4Cli+YL2+BP6ETNPoLqwyMw0OyROoTKc1uoGSfoo/4Si6tHGVh7H8LAClbhOJiWa0WSLX7J4pHEfqy0TOTg6PM9asDtU4v3G2q312qYgr5AzsklglMPPv9yRKyUom9cmIKAspX3OwcFBRyII1JfFtUt0gdvPjTY0pYbxARfdxshAvTQldl9rcA7maRGTFBXRdx9VsHC2Xk3hRlb4HKshwlYOpMiZevoPmRgm+WyT088eKedx0HcFAFijM46aLkXUtTU/YY0BjJBsIB5wwJDULjEQyDwuZIjHxlcSbJ+MpwySZWJR1xVQaePO46e7cOWM5HBE7OkMUGun89eZtVmyYGPO4ad1ymKUWYSHfRSwqAzPNj6GjcETexA7DKpaVkCX534mD/KZBKyZMMgPmlqhfDpaZ1+Py3E/aJfzSBrk4b5Cn7a94rG9EfLUM8k3A9wBvBK7unar5v7fxNcazT57jjy9N+TXz37Gkr3MseCvHstuwU5vdxrPcKD/E749+jEed2/iI9g4WuzdzNJW0rALBY79Ka/95mjdMSdH4ZP1V/MHi29h9sceu0QkqQcLe4vUUjAoPOxdpOy2+bfr7vE/o1EcHWXc7zLQyO7QRyxuXGB01gYRnIrhparFmN/kWLE6JlM16/mW/nuOcH7+Ws/oCf8G4gqqNeLZ9I2Z8nj1JSklmXBRHaRc/x2LPwlsJGJ8YIJTibHE331U/BVO47CyzM+tRyASimRekk72TLLgLNN1cBtBut182eQWAsfKFDXJ9qKFlCsMZE6kSJRkxKFWYBRUqjSGEOUu+pde4NX6MwM63/CxthNIdyBJC06DUM6ntyAtS37Gpq3xwo0HMLClQuxoWMr8RMIcOWWbgWCFpIMiMKU1pgoRqZ8DYq5ANYdlPoQjdSh0FWJ28GNatARiCKLVZ6HZJzZu4bOZf//3TU1yixcjp4pnziFQrZzBWZhvQhER61EZdfMMhI19Tlzql3hl277gDgAujC9y9924gt3o7cODAS/SubON52K7Nr2BEZ4fIacKGatPTyyTlM7z+SYXS4NSeXZQ7F5lVGkRz/fEt7mOo8SrgclA/y6/yF1nONIQQuItD4gx6/RsBWCdjubjCJPUZayeBQwxLVQ5fjjjpXEJOBULEBLZg0ZpxUeYuNzvSI6xV1kAqOplElixWx0MmSZ/VMEEKgV/wsEdtVqsjonaVma0xnlu8RXpElCxS1McYSYA1r0OuM2YGLIQR5mLOZLqmQzIP5CiERUYFgWxLCjiYKqRTyplRNw7pFoqEaYiWFNGdCF/E1BBckh4VK9cWFwObqcwbUWnOGV5ZR3cGaEqBoTMlYykto2UDpN5CZgn63HdeGibppIRXDxkJgyJ5nZ6QExM7gymPuAY6YMwlc2NdUtRcYtOgGOYzO8Jw8TMTCvn1opBpZFlOZljSwtVHkK0yikvYTsooDtCyjGDqYAOiFDGeWXmDnKWgv3ArdzVuWsgJBbOAqaZfQWKx3SB/Mb7aBvkvAvuUUvFLuZhtQJZKfuE/fYifL/waTa3LLwV/g0/u+RMOaWc5kBZ4Wjb4bPh97JkEfLP/O9yu/QSxs5dYHkYOTrF82wUMV+ILh65V5e/v+wc4acrg9Jh3DB5EE2WOVO8mHF3k9169gKN8Fvr305ztxI3qPFvbxCallWUsbT5F9106MvKI3B6TU1WsxhEqaARBzPo+yULUphaMeTZw6aQe+w6dQ2iKk8Y+mv5nuH2uP74kD+LbH6M1rGEdAuV3KQUxp1Z3Uc8+RIKOk/p0aNCISywfzBvik/2THGnkdj9ZltHpdNi//+XLrTGX6jhRQng1bnpsQqbQ7TxuuiKnDCo1Ut+mak4wJ/nrXTNrlEIfTIlSBgWtT18ro5gQmgZyYGIf3KKUKNqOYEFCAiwgeSYt4Nr54MlVL2Rr5iOljm3P0DKX2O1Rm0ePlgZjhis6AkFraiFakpFXJHQc7DgmC01cd4SydUSa4o59pNHispE377f1znG2vsTIPQ96FQBfy4toxe8jlCQSNWqjOWvkFDHJG+S93dN4e1/HgrvAhfEFisUilmVtD+q9fNiuza9g+E9sMdSmxKbBWSHIzAG3nZeErSKBoVOZTcnKTS7XllkcdFlptIkuvYaeOMENIuIJuY8jaUakTVkpJsQzxZXkRgpaj87IQa/t4aQVIVSMHWvMqgZLUcRHS22E8NBCn2Gi03JmfD5eReiSMqt8vNLFG88dLEomB8+PGCddrvMDAqeI0jS0OKRu+Ux6BWLXZosmCRkgkHED1xwhwgA1vylPrQgloRKnsHwrAJ7l4s+N4s0wDwsRMyji4qZbjCo5q+2FM/xWnSDzKcVlDDskIKaqoPtFcdPd7GrcdN6Q+lmVip3/XghBoGTOIGdrZPoChSRkZNroSqAMk2xSxNW2GAiDqsgb3qs7h6tRSFadN8hZ/rpGuqKlF0gM41rcdGYUiFMLvZD/3aKEcZofy8kcLGOEEWeM4xKGkxKRM9zTiYsN6KWEycABV+VNcnnlBT8/1+Km4w4Np0GUDuhkq0il0MTcgN9rgGbAZFuD/MX4aiUWx4HqS7iObczx3l/7E95tf4xV4zy/mb6d0Y4P8e837ubvX/oe3r72br69vZ+/M30fb7F+mw/XX8NvFP8al6SLJT+BXbpCR18kxqRvlfneAz9Du9Bi9Wyft7U/jplmHChdR9GsMhyf5cGVvbxWfor/kenctflGFJJnZIk9ok9x6uFmHfTdMzb7Sxw0J9hXiizaB8lQTEKdZ5YrXKefYDRYIvEVBwdXWFjcIMksLtQWKMRPcU8UMcls1lRuwL4a64TD/URqRnGeQFcMtzht7+T28UUkOkm0yl137ydIA86Nzl1rkLvdLlmWvawMsl6yMXWXwM0b5NrMRSagWRE+HrVsyKBcQ/MVTWMIswwribhi53fuBW1GoBqU9S46FRAQWAYMdWSxx0Io2bIF81JFSwqyeVhIaFj4xbzIOmEfmRk4zgwr9Rg6a5TIt9tMP6Jfzu91jWiZGn2mjsO0mHshZ5MyljdAeXMv5CAjMxa5YhhI4OikS+AsM7F7TK2cTZAEhHaVJLBYVAP6tKiOcr1br+CBErRpQu8MkDtZXBxfRAhBo9HYbpBfPmzX5lcoZJwRHO/x+fRJEIKt0lkWBorqFnSqy4TzbfekWOFErcb+/lMITeH0D6Bnj5BKja1kD/vjjIn3AEumojGO6Sf7WDRPUe8KtOIij1dy9rMerrInzDchQpUQGBJb+qQDSc0KmM1sjIqGJjQeqLdY7M4dLIoGB4Y+iYzwopBpsQZKYSQ+JTMi6kZQyC3efCPAiSugTIoqIYlSQjOvY6EjyaY6GqCt5rtSBddDzOUBWmgxnMdNF+IIXSl8J7/JLwZjEtNiSIQZVXDMPG5aCsmYCs153HQpLF6TWEjjatx0GdPJCQFNZcSppCQ9nGREZrYw0ikdR2BhzCUWedx0R9dpaPkxtGwIwI4wQ83T9LwoJzdGpsA1isRzqYWZSBLDI5YGqT0DoeGkGXL+fjqZg2ZOsMmYJgXMQkpkzNP0IhM9lejFlCDOj89k48t+hmw7v1ZG0RZNt4lMu6Tqi7yQNQ0KC9sM8gvgq22Qq8AzQog/3bYSeukwG0U8e+Ekr3M+yieiN9KobPKD6z9JnPwVutES60GFSfLNbMW/SHv8d3hz/0F+cPprrFjn6BUqGE7KsrXBJ+t38K6lf87Z6m6Wh2OWjj3M7tlFCtZBbqzdS9A7ye/ddYhUGLx18AE6mkZzeJh1r81MaOzR++y4tIF/g0DTJc/MLJpdnVg4HKTKWU1xqaox8Vxu0J+iE+zkpL7EdeM2VAKeGb2WxBAEyWVuDSLOsIdO4TxaJthRjBld2IfUFDNR4lbtNEtyysPVm9jhz7e+pMvqSp1n+88ileRIPW+QX24HCwDNNdCcMrGZf1VKoU2Szr0wTX0eN13CCGM8M8KaaRSjGVeceYNMwPrVND2RbwfG8zS91BmwGCq2HA1zrrOrSw2ZVCgklxm5BWaeQCGwowFZYqNpkqZyuGJt4MkylkzIEo1udc7CBK3cC9lz8Ese6AqGDmaxh+nkr2GMjS5NpOYyNHT2hxNiaxklFBetGqaWgYrw3RbxxGRP1mGNJay0B0oyrAk0abGmFr/AyeKq1Vur1boWB76NlxxVtmvzKxLh0z1UnNFmSCdzSaonePMz+e9O79iFNekzK5SZNpeJdY0beRKV6awMbqGqP80HuRWkQ1l6sPQImoBdXZ0ga1E2L7A7zBusZ8oXUVh42RGuG+cNsp26IASeM6AxihAC4qGOXfTIRJ9HqnsojvIGuaDHFGYSTSqMTDKs1jHTmIIVI9CIpwZGOSPCYmyNsOJ8eLecTjASybRQwpYxiQvabN6SNHJ5VqFQIDHyxlXGFsNrcdO5NCGds8tX0/S6lsQKK3jGc3HTPjUaYkysEpy0jK9ASlBavtuXZQVcdz48l4Vkcy+3RhggjSZ61qdra7hYKMMmmb1Q3HS+47ccKrDy12AnJQrBjLFlYmuFPEUVKEz95+Km0xjhVLCTjCAxEErhZA4YU2wk08xFL+SyPCcMmcmrcdMpcXC1Qf7yzK81t/CM4i0aboM4yq+hW18ssygtbjPIL4CvVmLxEy/pKrYBwG/86h/zQ8ZvMcyadMsG9wz+NhFjPrn2nxibkoqzzApjPLPCLu01XJge4bL/68iFEUGxyqXym/iIdgfrvka0r4mmYN9nPse9g4cIvDqvLd2ChkY4uMAfHvkLHFWPcXawxd7gFty4yrGyj51lLKmQ3ZceZvi9NjJVtI0x9pUyUWU/R9D5bBrTXk4RSnKUxzkx/CbOaQu82n0W6hOOr9+GnqxRTyJaWcqnxM1slE7RGlpUl0L6x/PCeqGwg1fVt3CzjMcrR3hD9zimSsnmd+An+yeB5wb0Njc30XWdZrP5sr0nQhNoXgVdBsRGgUJoMJf5ouyERjhiWncgzS8ihcikEo9ozzXTZTXhErtZ1LcQ2vUIBEqAHsi8QR5KnikblE2LURJQyQxQOlo0YOJ4ZGaP2CrihH2mYQlo09J0Lutb3Kk8diUbTJXNVsVBERBN6zTpsOnswHcKCJVhdIG9feoypgtcbCyxOOihtAZr5gWW4gmZmd90XNJsdhgRg9jDd8rUehn76PM+buOOkk/RHzGsGeiXXfpWFbn1GQD2VfYxikb0gh4LCwscO3aMIAhw54M523jJsF2bX6GYPrjBJXmByHN4Rs+Qxoh7z2XEVZNOvUrl9EVGS7uYVZcxsoyj5SeR453EmsH12jn+X/FXWEk1hNDRVzZzD+V5QMhQ9zlkrqKU4mzxOEosErk7uXGY0jEGVGOPNglerUNrHNExHNLAoGI2QFtjZuxGziZorkY9nCJThRcnCGBQq6DHAWUzIklqIAWiYYIQ9JwtVFLD00KcxMeLE6atIlU1QfMURl8iAa2aR9gXS0VSDYrZjDBxCXKOASfpAw7aXLLh+c/FTZtxlYI2hbwiEogGTUYcExl2ViOPmwbHyHDEiEQW8ZyAMSZmEiDnWuBmGLNWWkFlHbr2EarSZWRYpJM8ObVrCZyZRLMynHhGKiJasYGy5wmvaZnSdMDE9TB1h8DMm/nSZEy7WsUESpEAu4wRx/ipiSnBzmx8w8dE4mcOekmR6BrVMGSg1TAyge1mDKIXZ5B13cYwKkTRFg2ngd89CQVoRwk3FJ9Xm4tLMLr85/7MvtLwFRnkOSvxI0BbKfWpL/55mdb4DYFgGlPceowF8xKfNY5y7+h7ycSID1z8PUZJl3TWodc7xlMbH+DBtffwSPcj2GaVfeUfpXfxKCcfdrj/tMckfoLwyAHGToG3fvSPuHft06zXHG6372TF24d/6o/5T/fezMwo8N2T3+OPTY/bN95IrIWcSsvsFn2KfomSfwV5KKTbX2av28G7UGapfBMagnCqcWrJ4kBwBnuYkfkmaSRZvekCACes/SzNHuPuIJdVXM5uoVfcZKnv4C1GMNrCTDOerh7gUDlnAjbsBTazKoVMYDWeG9CrO3UWvbx5W19fZ3Fx8WWJmH4+tFINLxzO0/SeFzftTKjM8mI6M3WUAi81KMcDtq6m6ckJG6pBWesgRPHaMY04JbVzBrlva1hGicSYUMjye9bEj5k4HlKLCO0abtAhmbQAaOiCy0YuYTiIT98ooTQItIRR0GSBLcZmkXGxhIgVVidGMxL2RLmGeK3YYkdnk8RY5oJhUtaGSC0fwNk0JHUrZ0V810YkKQeSLXwccHUa/S7dksJIikTYiOkGhGMOVHPG58zwDK1Wvs5tFvmlw3ZtfmUjXp8SXxzzhH8MpWBYfZrWEFqXFd3GKkngoymFaXucqC+zc+si1eaYtL+PgXoIU2Q8ofaxP1UkImShGuP7cDG8FUHG2dDCrO9nU86I1WmUchmUKtwwzHjWPQ8xiDQhKkp26AHnVRWAXeoAAydnS0dRSlqyqE+GxDKkMpdnjKouMgxpWTOSINcIU8mlEGN7RBgtUDMmGEmIFyVMSiXqZgfDUthxim+6YOQMa2GuMa7IGRPlMi7M2dl4rt2NApTmfknctCVidD2Pm06NGnWmTDWBneV1eZoJhJ1R0AekskTZnJLqOlY0I4vyIKZmlORx07Tp2YKy8pCGThzm9T8o5Ladhitx/JDQCKkmDhh53LRMixSCIaNiCV03CecSi/JoRDKPm/Yincz2MKIIP7NwlMJJPUI9zOOmlUlWym8ubJkRGg5GpuM4GX5qouBFmV/bXiCO2ix4C4Rh7kr0glZv2wzyl+DFJBbfBwyAfyqEeEwI8StCiHeI58eCbeNrgt/+jQ/zDvu9rMe7OBq9DYXNx6/8d04tr/Lf3/KX+Hff83/xS9/7f/N73/aDXFlY4fz0Cf7b+A+ZmJLXLb+bxUNvY3TkJs7e9FcJdYO/+IH/yK7LT/PQripvEG/mpuotjNqP4rf28r4bd3CDOoa5eQ4pbarjfTxbvkKMzn6jy86La4TXgWEnnJp6LPZ1zMjkkL7CZSHpGILTizVush+jN9xBP3K4Y+sMzUabKClwudagGD3OfUHIJLW4LBRKKFYnFlm6QhoPqfoh3VIFPbjAWHgshlu0aaLHVXYcyhusk/2THKkfQQiBlJKNjQ1WV1df9vdGL1dx/R6JVc7jptPn4qYr8zS9UalIFmsUMotS2qVXrJOh0UwHXDFrlPTeF8RNC6FQWUBz7hsaeQ2EPsCcTz7PfDcPCxEK36vnYSHDfBCjrkvW9PnUtJbQ9uo0xkP8uRfygtxECY2N1iJaKrDb+VbioTQvgFt2Lbd6s3dzzjCw8SmmXQzp0bNGNOz88VMnvxAc9K8AkCmX5mCLtuNipMWcEaIGnWeuBbmcGZ5hYSHf1ttukF9SbNfmVzBmn9sgzEb0KhbnVIGkeJK3HwehBM/u2oM+HeB7RZJKlXMlj8OTJwEod2/Eyh5lKD360V4OpBkz6wF225LSKGYrOUTTuIDR09Br+3ikECNURCHW8Ys6KxGctdeYkqKFPn2VD+hdTHJZxJK8gXMFIJP0pCIrmayMB0yTAbUwQQHjShEtCli2R0Rji8iymDk59TsxJ/jxMlXdx5UBhTTFLxRoenltKscxSeG5HcJS7bkGeaxbTAs5eaIlXXh+3PTseXHT4dW46YBAxJR0m4JSjHQNS+W1aSwFupPiaX2irExRCwhdBzuaIvy8bjUjMY+b3qRn5Wl6StNIklwON88dQbczzCBmbCbYWQmhJLYhiKSLHQ8YFssI3SKcu3UUp2MyTaKEhh3pRI6LFs3mcdMJTuoS6CEaGREmE72AoYOlMpTQQDo4Vp6052vWV2SQAWxrgSjusOAtoMmckHpBJwu/C1nyAkf4xsVXbJCVUptKqf+klHo3cAfw28DtwIeFEB8VQvzYy7HIVzqyVGJeeZiGscZUvBMlj/Ds7KP87j1v5D1v/37O7j5EKVmnnPZZW9nL+775B/jsve9ETa7wyfO/yglryDdH1/Ejw4N819PrvPHDD/CovJEnjtzEjyRv55bKDfT7x3EGm/zzW2v4hsdfm/4mvyWavPrK2zCkyeNWmZKIWZIx+89+lv7rbdLUZFObcaZfZOTs4EYsniVjfTlDCcEt2mN0Rrt50tzJYb+HqPg8Pb6PVBcEyQVeFUQ8K/fQdc8jJOz2UqaXbyTSEkRqcJ24QjXs81jxOu6ZD+il0Sqvee1BwjTkzODMtQG9fr9PFEWsrLzwtO5LCb1Wxwum1+Km167GTdtjSn6uVxuUKqSBRkGYeHILpeuMRZXFuEfbLlPQewjtOQY5NHXoaTSSuVuFU8NiiJA6KBjO6syc/GLge3WsZErWX0ZKjYqZ0hU5O7+sK6aWx2K7zcSBKIMVPy+C682ceXc3cj3eLq2H0mBoFFnptIntHVw28qJ9YHAcnQVGTuc5qzcjL6Krfp6MmMoKjUGHRDcJjOes3th6mobToGpXOT04TaVSwTRNtra+skfnNv7s2K7Nr1xko4jZo20enHyazDQ5WdxEaTH3nE2J6iZbjQblYZdpbZG0vgOAO7TPoxKHhfFNrJrP8Lvci65MKpkLKw9hCNjfSxjGe1iwTrJ3bCBMh8eq+Xe0Fu7n4CxnNafCZ2ZIbBkQ9BUte8bA9zBKEksUeKxapNGLUIAqmRwejxnHXSrTGaFdQOo6WhTQsn2igcS3dbbEAhmKWI+JomXKxBhRgD33ey86+e5WKwox63uvnYtiPW92KypgottEtkumA8kIUwqcJCYzXQrTCSjFzCsiw7x+5XHTeZqeLk1Gho5zNW4agShIPG1IKCvEmMSOhRv6GLMeEkU91pFagVis0bM1vKtpenl/jOHm1wHLytBmGT0bMuq4yRTNFMwyCz0Z0S9XkYZBNG+QrzbzyjDQYhPfNRFJgCYVtgxxpE2gh+giv7ZsxA2KVoau8j+ssrxh1gzJWL24+4RlLxDNGWShYjxN0Y6+TFjIdLtmPx8vJrGoXf1vpZRUSj2olPonSqlXA+8G1l7qBX4j4FMfPcFbzD+lk9xKQR4l4QI/cestHD9yB5X+A9TXfohs/NPI4Y/TWPtHuOEFHrj5Vo6//vtopCYnn/1VHm1/kIP9gL+3XuMfW6/iP7qH+AX/jSxbTS5f/hDu5Sf50I2Huf+663gDH6V0eYN1M2ZP504ulc/Sjksc1LYoTsp4WQd1XUC7t8ohs035YoVa8w4MBNlYcrkpKccjdscXmAzqrKclFnaPUBWfY+Ht6MkGe8KAssx4Wn8VG6VnaYwt6ss+k7XcyWHLanGHfYoWIfc376Q+yZs4lbksLpY52T9JqlJubt4M5PIK4OvSIBvN5vPipmesoaFUziCXrsZNlypEvkFRM7BVXrAG87jpgW1jihilafmWmFKEpkG2ZVHNroaFVDHUGKE0HJUxiiroZs4uzwpFBAp9UCBNTTw7IJISJVKac//LamfI2NOQKeyYs9qb9SYKMHr5Gkv2CGXpZMKgNhiQGUvXvJDv6J0ltpYYuR2kkbNFvh4j0XBmPiU1Y0qTxiBnV7rFEihYZxG2TiKE4ED1AGeGZ9A0jVartd0gv4TYrs2vXEw+dYXE79N2U/qZTdr4PNdf0qmsQ7u+ShLO0JTCtRyeau6hNehxYPEi0WAPbXuN3VqbD4nr2ZEIBBrmjk1SCfrWLiQWsdFjt8idI05UnkaKIoZ2MzeM8obMiwsgBAVvQLWfYOkZ0cDAqLgoEj7d2EWzl9cYVdQ5MIhIVIwXBkzKdVAKPQqoWz7h1pS0qGjTJNISjMxGZUW8TKKCgMzMdbSZHaIktMIEb+X2a+eiWM5p2iIRE93BVAUmHqhwii117Gtx0zFOnIeFZH4uzzDshJmIqCOYUER+Udy0KilsbUAgq0xUEenmThE6KSMRUU9twCATffomeOTHTTRQGTg2KAW2mSJ9QdsUZKpOMR6gbJ0ROkIOSEyTmW2S6hqJpmFHOblhWQZ+YuGX8vpspSlWNsNUOpFIrjXIXb+BZ4SIedx0luavwfBSRlL/KiQWi8RxlwU335kta+kLhIVseyG/EF5MYvGsEOJpIcSvCSG+Xwhx6OovlFJdpdTvvsTr+4bAo5/4LDutk8zkN6NUk59cijiz93paG+9jdfwf+YHZjfzo8I380MXv5rUXD2P2f4p670N8bP8u/uu7vpdDlXtpD57kjy//Eg+038fZ0cNcGj/JE5sf5PznfpbFyOD0Dffwi6/aRYMuf3vwG/wWu7ml/VrstMDnSxmg2G90OXTyUWa3aOhmxsmpi9YxKEwsDhq72RSSmdJ4fEeFW9WjTPqLxDONG7oXaN50DoBj3n52zB7hnrn++Ep2F1ulKyz2HYrLPqrXQSjFM+X93NPIv4yPlw4z9AWeTMjmGrMnt/Itw5taNwF5g2wYxss6oHcVeiuPmw5tDzOLiQMDMW+QC0F+Vz8oV+hHVWomqHlCXlersRD3mFq5/s4wfKSeF9nINMi6FjXyhrPnWOgyL4AtkeAnRVw7ZxpmxZyttcYJSuo4zhQt8UicPrX5NHS5P2JYzL2Q634RW4UMC2Ui20ZhkPkFHG+EcnLGxpglZOYCV+ZeyLeM+/juClNryNDOi6VSMwK3hT8psle2aYslvCAvxt2qiZAm59Uqsp2nHV5tkJVSLCwsbEssXlps1+ZXINJByPTzmzzW/VOmlTKPuwGZMeRdT0mUpnjq0BHMYZdJsYLhuTxeK3No43HMYoTVvQ4RfwKAU3IfR2SGVCGL9ZCJD2ejOwE4mdm45V1MUp+BdQKlLTIr7ODGQcoVc4uFKN/pcmtt9oURQ90kmZoUnTpolzhbWMEaxQgNKtLHCUGTEiOT9GoNrDSmYEUYmiIeglaSTCgxMSc4UR0QlFVIHCaEVl7bAk+SzXQ0BdrKc0GQVxNTPVIyzcBKS4wLQBjhKBNLZoROAZHF1+KmE39uZ+nEhORhIUNZxNIn6MrAjYzc6s0A0xqg0OnLBXAFbhCgnpemJ1Ruw+YLhXstbtokCQyqOsyUgWckIAUbhIDFctgncTV6KPS5T/JoTkREpomV5M2padtMU4ugnM98lDMTM8uJIiGeS9PrBQ1c0yebPy8O83OiFxKGmflVSCxaKJVQt/L1eyJ8YRcL2G6QvwgvJrFYAL4deAC4B3ivEKIthPjD7S28rw26m1Ney8eYpbdicITHymt86ObbWGk/yt8xPso/2jXg6HWfZddNH+C6e36D19dn/NCJH2F181Msbv4qx+oL/NTb72Lf0e/jjebd1LubxOc/iTr7aQ4OU/be8nc5tlLnn9xaZlKs8Lflv+Gxcwc47Xa5ee3NbBYvcMlfZpeYUElt9l96iMEbDaLIJXG6nBiV8J1d3CxsjilJezll5tjcaT1IZ7SbY/pObu1fouL06EwOsFkrUow/z2vCkK2owFAFSE2yMrJAayCDLSp+xLnaDipahwQdTWWssYST2nhLObNxrHuM1eLqtQS99fV1lpeXX/YBPQBzqfWCcdOGPURLHZwszRtkv0rFjp9L09PqLEZ9Ajsvjo42RM11yKGpI/smltOhlCi2bIGmcs3vopLEaZmGsUFomEyK+d91gj6Z1LGdKUZWYOJuUJkzQeYsYjD3QiZYYZENxq7LpFxAWSDHRcxCH31u9ZYkIJRBaJSY6hr7oymJtQRCccGoY2spkDHzmsRjjT2qz0WWEfYMN5jQbyj0zKVHDbl5AoCDtYPMkhmbs01arRbT6RTf91/6N+gbENu1+ZWJ4QfOEbSPc6luMpYmk9b9VCcGR84kTBdLzGyT0mTAtLmCXltGaoLb5SMArG7dQ0t7lE/KG4iSBfbGGqH9cVYsRWUYsxkfoWZcwt8y0esHeNxKMdINNGmwWfe4fpwP6KlIgyzDLyp2GT7n5zbbO9UeEnOTTNMJ/BRVMmj5E2SSUQxzB4t+s4oWzShZIWlaRqYaRkMghUbP6aLFdTQklWSEk2RMiyW8LCDxBGJy1eLtuSAoy7Iw0HGvDrXFFfoFkEGKi42pUmZuEaEkbpQwc4uEQYZSGpoTE2oJdTQG0sMV+fBdKbSZyLzWKjuv1WPZRLgKM01RusmElHpaRs+GZFoVX6Y46rm46XRcoqQrJhgU53ZxfS2Xy+3xx0SeSQAY85o+0jNMzSYyn4ub1kyXWWoRlHIipJQZGHMHDVuZOCJvlgdhFdtJiIK5dd0kr/miHDFKLPB7kEZf9jNlzb2QDTnDMzxMOf1SicVVBvlFmu1vNLyoD7JS6tRc6/ZDwDuAnwZuAH7ypV7cNwJ+53c+w232p9nI/gIpNX7ycItCOOUfFn+NffVNNi7fzGMPfiuff+Sb6HR30zr8Mfbc+2u888wPcmBtxt61n6NjuPz1e3bw+esz1A33sXLLX6N+43dxZXmZ/5J9mp+8dx9ry7v5W/wC+89u8RnP4o71N+MkJT7dGpIpgxvMNRauTMmaEmP3jItbu7hxMmbHZoGl5l3oCOKJ5NyygZf43KCO0e8vc4Ymy8WIpBnw6OStgCKLLnJrEHJSHaJdPIVQsM/OGF+6jUjzcSLFHrONHvQ47u7ndaOTjCkhoyUOHc01dU92nuRo6yjAtQG9r4e8AsBczuOmo3mD3BoIhATDGZGoIuU0pFdtEAQFKtYUfa4xWzPrNJMBiaWRKpeS1kPTSigBgWkiRyZqHhbSdgRinmy0IDVUUqOUXWLsFpgVDBQCN+whUwvDSGkomzXnMp4q42YhSarTqc29kGeLLLLJxPOYFYugSbSugVXqUJkn5F1uLLI46IJosGboLIkxmXHV6s2hauXMx9QrwixhvxqwRQ2jKGkMtuhWFGZSIhYOWTiGaeeak8Xp4entQb2XAdu1+ZWF4Oke/mMXOLH1YUa1Kg85PpnV4S9+3kD34fTyIbLJCKlpFEyLxxYOU55NuHHhWeLRMn3d5KB+kd8Rr6KcCTzpInc+hCbgSDdkmOylZT7L9f0Iza3yUC1v6KpBFUsXNBLBJXuDsUjQwxmDxGTJnXA+zUmKnfImrhQCUIp2kpJWbRZGfYJ0Rm3uYDGsesggoGX5xEGuH1b1vC71nC3iuEHVmGLEAcUwd7CoiTF6QWL6Mpeg1Z7TIAshcA0be96peGGZgSdQvsrjpqVkUHwubtr3ikRZgEpK6E5EKGLqStCTRcp67vxT9p1rYSHpPE1vmtUxnVzSoCOYoahlZbRsSGYsYmQxvpnvHErDJB2V8DTFUBhU5ixxrPIGfHfgk7jzXcMkt1IbGBJHLxCbJkIpUKCMIpPUJvLmjbsCLcnX46YujjlERzKMKlhuSoDCCQKmk/w6pJUTJnF+br8S82vbeS2O461ch5z12YoT1FzTnP/xJRA6jLaVWc/Hi2mQ7xVC/AMhxH8XQnwe+BlAB74bqLwcC3wlQylFs/NZlFrFEiu8f9lnrd7gL6vfoW4NOPvZ7+S6n7/Mt/7Oh/n23/wE7i9rPPHo67FLW+x808/x5kvvYs/6Erdt/iTedMz//+5v5R/euspPN87wr2rP8nNHq/y7b383g2aLH1b/kru2HudPO9/JFaPPjetv5ELtOJuTvbQIWZQRdz3yP+i9xUIpwZlY8djYpTB0uMnYyXGREUvBoysFbo8fJh5UiAYWRzoXMO/pIwzJ4/r11PzT3DbzMYBj+n1cKT9Nc2jTXPWZXGqgBGyZLe61j7OYzXigcRvXzfICoeIW996zl83ZJlv+Fje3cv1xt9slSZKvX4O81MQJIwI3L0atkY5IFbozIZAVanJCv9qAQKdlDBDTBDOJuWQ30VB4WkhfrlDROxhzNiY0dcRYI3X718JCNA0UkprUUWkZM2kzcTxSK557IfdI5xPaC5rORbONlVVYyvpMhDv3QlYE0xaLbDKyi0wKJUSqsLZSDK/PjjAvwBfKS+xurxMbq89Zven5V3pTT2jZ8wuHm5vXH/Lzwik1m1a/Q9uzMOL88Vs0YOtp9ldz5uf5ThbbOuSXBtu1+ZWFdBTR/YOn2XrqP3HyuoNsKYvp4ico+w6vOTsjLmmc3r8Xb9Bmc2kXO2z4bLPCkQuPUWiNEZ0jhNkn0ITiIQ5wZL6Dbu3uEGWg93aQKpfAGLBPyxnIp+rnUAgq6a3cNMybw0RJfFPhqClhN2PBmdILCuiexKXGkxUbcxKTALJkcXDSY5hsUQ1ipBDMigW0KGCXMyQa20SmRejlko2JNSGOl6gZE8w0oBjFTEolmu4mmgFulOBbLljeF5wbz3Ix52l6buQxLAIzKCoXJ0sYlq7GTfv4bpEg89GjMqaVx03XgC1Zoq7lN+uVwGWSzc+7nksBw6yC5eSsqoYkyuZx0+kQaSxgJjO6tn4tTS8eF7EEdDWdhpbXSjGfJ9kVJjD3QnbT/LWMdYWrl4jnQ4lmLEmNImFmkjoTEBpuKpFRzgR7qYduTnBJGcVFjEJKZBq4QcDYdxBSoRdjgqteyOOvkKZ3NSwk2mLRWySLtwikYphmzz1I0/O46tGVr/Qx/YbDizHI95MPfLwXeL1S6t1KqX+jlPqcUip+6Zf3ysb5ZzrcpT3I5fTbyNQu/sO+IjvDC7ze/TiXH347d//Bxzi/fAPrd72bK/cdpJGMeNtvPsgz99+D5Y7Y8YZ/xr2X307lylG+M/kpvu34pykYMQ/c+SY+9ppv5dK+g7wt+Bj/Qvs/OTw4xX8+9o94ZPFPefOZ70Ei+ehiSpRa3GRcptJX6HpEdFdEp7fKEXGZ6chDlY6yU5icTTNGywFj1+YO70Ha/X2cYJm7O2fZXX2GOC5wqr7ADv8zvN738TODdnYjndIaK12H8s4pqrcFSnGicpjXVNcxhOKhys1kwymakqRCp+BaHOscA7jGIK+t5c3Z16tB1isOlmYTOrmEoT7zyFKFZgUEqkQj69OrVDGClKY2RJ/pFOMZl+2ceSkx45LaR01vo4kSAkFq6OgTNU/TyxnkouGQGgHlLC+i0SxlYudeyIFTx/PbRJP8mC0dLhldBBp7mdG1KthpRKil9P28Qc40g7WFJbRAYW/ECKE4nOQN67rbYtf6Gr6zl/OmgcMEJ+5gygp9p0sll6sxtvMiuntyAchTp+qDDpFuE+n5hW+LJrRPULErLHgLnB6cplwu4zgOGxvbW3YvEbZr8ysEMkzZ+s0nmX3mP/D0kk3oOHy2cgFpTPhLn7Jwe4pLK/vQRj3MNEFVmgwb15Fpgrv8zwKwtHUPy9n9HMt2M412cVBlkFxmTy3BHytOxXcB8JT0KFb2MEt91rzjKK1FbB/klkFKLBIqcW7fWCh2aAwjLE0SDQ3MioUk5qPNHSxv5R8vVTa5sT9mkvSpTKcEbgmlaehhwKIzIewppq5BT2shgUAPmIY7qGohThJQkimR41B3cvazGkekxS9NSfVsD32emKeHFiNPIKSgkCSYMmPi5k1iaR43PRBfGDethGSoatfipotRkXGWtz6pPk/Tk0UcJ39dhozJUomlTMrxJE/TS4e0XYGLmWuQpzaGgA1DZ1nLpQ9WPARgR6hQc8rbjsq4oc/E0HF0LydGgMLMJ9VzwsVOY4Rdnqfp6TBP01PGFIeMcVpEK2WEpo7rB0ykhZUozGJK4s/DPr6CNOL5aXoL3gJRlDfB618ss6js2G6Qvwgv1iCvAD8L3Ap8SAjxWSHELwkh/ooQYt9Lv7xXNn7/9z/JXus0Slvg/SuKXqHAX7Z/h83zt3Pgj05x7K4f4PpXfQuf3Pcw//bmDU6+Y8DmXS5v+oOHOffI7XiVNkuv/jfcsfY2us98E/cd/EV+nJ/ll07/IL9y5Yf45ez7eXfx1zl/eRfvffSfYC//Cfs372Vxso/793yYoL2fRUJ2igmv/8x7GL9Bw7BSTo2qrG+4HNrwOFy7kwkKNYGTOwp4ic9N6kl67VVOimVaXoasBzzVexuxpUPyKK/3Q87OWkz1yyih2D1xkKqJ9LcoBxHn6ys07BEZgq5Z5XLWoJiBqOVd2bHOMSzN4nDtMACXL1/GcRwajcbX5X3SiyaaXSaaR4iWAps0BSHyYbtm3KNfKmGFAbpQFEOTcjxmvZAXpoqacIUVKloHnmf1ZkZ5WMhClIeF2GaZzBjhzBvk6cxm4nggFDOviRv2iPq5BKVmZlw2cv3cbi1hs1BnubPFzJJMEpulMN9OXGstIRA46znLsVe0UQJ6Zpldm+vE9irnTROB4mj3CdCXGXib6EY1X4MeoxBUpx1MlTBTLZqDvMnulQqgBBfYgdrMb2oO1w7zTP8ZhBAsLy+zubltPv8SYbs2vwKQTWPWfuFTTN7zU1zUtzh3YD8P2QlZ/UH2tmvcuzYi9QRP3HAzxqBDt7nEPjXjo0uHaPU73LB8gSSoMFFVjhhn+CXxJnSlsxg6pK0/pqzDcj+kHV1PRV8n3AK9dYRHjRQjOY3Co1urcWs/5VnnApV5fLHd6HMgjhjpJvHIoOg2ENoFniofojBI8tRQPaKaq8lwo4hRuYFQCiMNqJgh4aZPVpCss0AsUjRlkCVNvCxDC32ElTeIrpvXseUwwGod+ZJzVPA85JxBJjYZfVHcdGLkzbM3n/3oWAorquDpz4+bbtIUIyKV4iU1ZgoyCZkuccSITBYourlUwkgC0ixnlptBRGq2QHbYcjSKygPTJpnlaXqblkYhk7mncjQlFSGLkX5tGFqkZcqz59L0/HmjXx6NSeYvqRhqKKeEESdMUxtb5hILacywkEylgyhJUk3DDQOmuoeZCRwvI7wqsfgKThZ5ml71mtXbzL8AwFr4RffR5VUYbzfIz8dX44P8XqXUP1BKvQ54M/AMucbt9MuxwFcqlFIc8D9PP3szdraf396tsyc7x6HwNM4H93HspjdwV+sAT1X+I/vkiHe2yzxeLfGJJZ/2fTZ3/+7TrF04THX5Wep3/DrXt1/HsU//TfxgAXc1Q1USTnRu4Bcf+nuIkz/EkcYDTGYVblt7K08vfJbz6W2EyuBW6zzN9gyTiMlbJYPBEqvqMo8JDTdZ4hatxqdFCnbIAzuK3BPfTzQsM+273LV+gvQ1M5ST8aC8FzOdsXPSoSwljxv3sl4+iZkK9lZCRufvItR8nFCx39gg9fscd/Zz3/BxNlhAi5ssH8rZ0Sc7T3J943pMPddxXb58mR07dqBpLyqZf0kgTB3hltFVRGwWKUYG/twMU9opjWBIYFmkKsvT9BKTStRnc94g1+SILaqU9c4XhIWYWUxqjlgIcpY2dpsYoo8u89c5mDbx7fymwS80MFMfNVggTQ0qVkRP5ANwSwaEhs3CVoeRC1Em2THN91g3mrm1j9XO11t1hmBp+MJhdWuTzFzlgpmf59dtXWDm7mLgbhLYy/nrU1MCp0E4LbBPbtJmBTfMGZ9uVUfLLC6pJbK1JwA40jjCudE5gjRgeXmZdrtNlj1vK28bXxNs1+b//TH6zEnO/NUfZ/rbP8oVO+Cz99zLBT1jbekjWFmFd35CUOxkXFzZA9MBdhwyWN7LfqvOkzWbG84/QmGlh7Z5lDT5EzSheEDs51Ci0NBh/7NIBTdvxvSTgzStk9w9DNHsIp9sBGgqpBi6DEo6B6eKp71zBGmGiCP6nsEuY8ZpcteJXWI/0ljHNxzSaQJFndZsjIoVZpp79PYaDaw4oOTECATRUGCUJCMqTMwJbtQANEoyJQ1iQjsnCyI7RsaCciJxdr36S85ToVgg1sHJApLEZjgvoU6SkwCalte2q3HTfQusqEpBm3A1bnqqLdBkhC8kTtoABNNEgJWn6SWySNmakmkaduyTxbnsrxWlSL2BYpOOLahKD2mYxEFeoyfF56XpBT6+OU/T0wWGgCQr4gZDRsUimmYSmvM0vfGQWJ8PHoY6qe1hxAFBZuJIiTtP09OR+MoiKVkgBG6WEBk2embiOSlBZiIRMFn/ip81x1681iCrdL6L+IIM8hrM3ZS2AcZX+qUQokI+IX3v/OdW8uL7R+TT09v4M+L0021epT/ElnoHzzaKrJU8/qb6I9rHvomOyPiuxu18pvff2DxvgFgElXDwWZfHjkw4pra44bYS+3+9T/sfNqnvepRx6LHr+Hdx6tElqsESuxzBnTZ8qxD81/qHWJuUeHX7bZytP8FDyzC80OCgGLFEwH33/xHjt2gYbsSZ9Sb6+S7XhSat1htRAoaTjOk+QWQavNb4OJ31vTyq7+a7Nj7JjuZx4sTlycYOrht/hDf4IakSnNHeyOXqv2ep61DbNWXrWK4/7lgLvN55nIV0yu+t3surplt8mn2ocIXXvD4PCDnRO8F3H/luAIIgoNPpcNNNN31d3y+tWMWJRsRmCTeCdiooAoY9pjrNmYphqYiMBZ40KGZduoWjpBi00gEdbS9F1f+CsJDU0GAC9WQKeIROE1edJZYGqIRhVMM28y3AWSF/ntHzyDIT1w6I5oMxLU0HCeXukGFxJ2Kgsex7mCqmW6mTaRoigiwycAsDVKQjIok7miL1OpfnXqRHp0Mi51VYfsxlcwlT65JImHktvNGIQ6rN58U+drqfwQln9FqSw+0CE72M1j0FScD19euRSnJ6cJqlpSWyLKPT6bC0tPTyvVnfANiuzf+LI55B/zykIRQXoLyDeG2DzY/cT//BhzFPHEPrX0EBj7z69ZzeucSG4fPI0mfQNfjWzxS5pXOJxNN49JZbcc6fpN9c4FA84MP73o6eZbwu+yxCKBY23kBV/iyfVjcwS3Zyg1JoqU9t1acbwIZ/lEzZtA2fu/RcE/t4M7+HqqZ30ppIDARbRo+S3sKMZozHsOhO+FSyB4Cd6S1crjwAStGJU5LFAs3JGnEWUg3zG+Bes4QIplSsgCRpoqTArmVkQqfvdDGj3F+9lo3QkoxJoYqhMgJPoSa59IDV2/hiFEv5YHM5mzHNXKJCzsLacRdYxYsjlLAp+PnQ4dA20OMyhsgwjJggjsGsU8Nnogtq2dU0PSg6GQWtzzSrUtFmnHaWsaIpKtiCMiyEXEvT23LysBClaSRz8jUtAW3QbYk5SxiXMppJFTOLMQ1BlLlYyTqD4gEwzOfS9CYjUpGhEFiRQeQ4eH0fqGDLGDfz8I0ATUik0ujQwNIV9tXmNfNwCvkNwURYVF5kuM5xVgnDdRYri2jZCB1Y/2IGubIDZAKzrXxobxsvKrE4A/wtIAB+CtihlLpbKfUjSqn/9pKv7hWM//6ez7BgTClQ47/sUpTkiBunJ7EfsLhv31u5MD1BezogWHwdwZG72TjyTnTvDdx6ssZH9pWI4zFhRWD8QQ2lNJb2PsbWDb+NMzdCvxCmPDYJ+d34PN6F13F9+x6eWPkYx5Y3yM7dioPkdvssNz3xBJQk029O6fVW2DPb4IFCxkq7xR32Hj4rMoqZ4sGdVXZMr7A/O8Pg8gq+r5Et1qHq81Tvm/Fdg0L8Cb5p5nN+WkNKwdQZsdp1KSwHiO4VNKl4onY9byo8iybgM9XbyIZThFJI5bB7tcKxzjESmXDH0h0AXLmSb/ns3Lnz6/VWAaCXaxSmXeKrcdPz/THdmVCdzv0qKzXSUMfDxJFbYGgMtTpLUYeOU8DVRiCeG0AJTYN006KW5kzIzCqjKR+BRl0LmSUlvLkX8rSYP88aZSglcJwpIvVIrRHNuRdyYTSjP7d6E+EqLbaYuC6zcgFpCeSwhFXqItx8+29kuRRCn1hv0jM09soRqZFHeZ/THCrm3MnCLaOmKYdUlzZ1ZFHR6m3SrijMuIIUOmM8aJ+4lnz4TP8ZlpdzFnpbZvGSYLs2/6+ItUfh994NP7cb/v2rCf7F29j47tdw+s4jnH3Lm5n9i3+K/eBHyKwSz7zpXbz/h/8BZ3a2eLp4ic+tfgTTiHntU3u568wAa6p48sgtWJ0NjDTm0t6beQMa718pcejccfbu6RBNm6wbCXuMDX6ZN6Ipgx2Rja5/iFVHUhiknIlfhUbKY34Bp3aAbjJm5D6N1Bpk9k3cOg/9cGOH1NAoWENkO6NlzxhOXYyKwtFKPFF1MGYJIXmC3p7JFuOkT30eTDSslVGBz5I9JZrlc6JqIZcAdN0tkniRkj7DiWcUo4RxpUxNjZEFgTGdn7/W4S85pcVqTg5U1JQpLpNCXuP0pANKUYgCpOFRnOYN8tg10aN8mNmy8rjpBhqOEgwNHVvldWmgBFohxdWGhLKKRBC7Fk7kI6Z5zWrFBkorEYs1tmxBYW71Fs8dIPRraXopmp/RsxSZquElYzRbYypN9HRIv1JF6RrR1eRAfwICNFNHxSYz10QkPppUOJmPk9n4WoDGPPTJb1KwEnQ537lMSmgaGG7GUBkwuvwVP5a2s0IYrucuFihqhnwBBnl+jd12sriGF5NYtJRS3wb8V6XUp5VSwdXfCSHufMlX9wrGLv8xrmRvoWcd4LMtjzeJDzM8cR8XV5ssCp3jw6eo7vF4lTbhpp7Ggc0GwREJtbdzz4kVfuWoRWFPj8bZPlsPHKHojji4eoYHb/2XPLTzj+gW1gi0GCPzONt8jD+8/pewowrphTcy1BT3madpjiccPPMM/XdqCENyZVDn1KkSO3yD5cY3YQvBqVmGtdDleNPjdebH6PV3cmVY45sufp7Zm6YoR/Jg9hrMLGFlco6FLOPx9CibxeMAHM4swsF1pPEm1VnIsFbFdCUhJjNhcTmtU8gUaSn/KD7SfgRNaNy6cCsAly5dQgjB6urq1+29AtCrdbxgQmQXcaKIy/O4acMZU55HtPYrVdJAo6wbmPM0va7WYDnuMnIsNCERevYFaXppx6Em8i2vjmMwt/tkSUmipETDaBPpJtPneSHLzMBxZphpgbG3RlUUEEoiI0WvmsslsukCi2wy9jymhUJu9dazMIsdKlrO+JxZ3MnOziaZvsJ5w6Su969ZvV0xEhbs/Ko1dXWEUhwJ8yIsMpuF3iYbnoee5hfCDRZg4wmWC8tU7ApP956m0Whgmub2oN5LgO3a/L8YlIJP/hz82ptIzz/IR4b38aFP3MaFD7foni/Rq5exbs1Y+aYB2TsVj74ZPrZzi8eiD/HHqx/lVOshSqLM7afv5LZnuuxpj+nXq5zfsYI57HBlz37um57jMwvfzMzUuPP857BaHYobr6Ll/z5T5fAo+7ghSTGlQXbkQQBu25zSjw6zYJ5ied1Hbx7kfkfHjE8BBTq1Bnf0Ei5Y6+wM8nDGQn2DPaMIIRRhz8CqFJAEfLS5i+V2zjrKssktgxGjuENtOiU2bSLHQQ999jgDoqFBYNvMnCoAI2tEGK3QNMZYqU8pjBhVKjSNDqYnsaKMUDfA+9I5k1I9rzEVFTDSLELXQWpAPMRQ87hpw8WbjfO4abeEDPJG1jBDpkQ0EGjSYKJr2FkDFIwyDcoSRxsSyApT5ZG5uVOEFflMREwjcVDCJGWLjiMoqLwOJ5pAZuBakCmBa6TIQNA287jpYtwnszVGaKBGRJZNYBpITSPWdeww3xm0HAs/tZhW8kbYSxWOnKAhyDSFMU/T6/hNimYAc7laGuc3DWYxppeaLzpc5zgrpOmQBTc/lyURshZ9MYM8v8a+SLP9jYSvVtT534QQ1zoUIcR9wG++NEt65aPXnnCb9gQ+y3xwxUEJwd3BQ2SP1vjO6u2cGj+GvXfMN5v38/pd7+Pb/v7d3H3wvRy4XCbduUnRfhu72k0+qAzit0858v4LbJw7xHJ1g6NWi8srD/BH1/8yJ5Y+yYmVj5PqU+499y6eiI9wwZC8RltnhQGv++THiG9Kye4IubJ2mMazAx7eMeX69VVu8w7ycVLqieL+A7twkpDXWx+lvbGfz5n7uH3S5cbSQyRhiSfrq1w/+hxvnPhEaByzvpXztSdojCxWdw3on7qTSI+Rmc2rjKeRwYiHizfwLaNHWWMJPW5S25cX50faj3C4dpiSlTPhly9fZmlpCWueAvT1gl5v5HHTlocT+WyggQLdHlPx8662V64yCMtUTY1EzQdGtDpLUZeZnTeuljFBGvnkcWjqpD0b021TTiSbjkCJ/Cu5JAUyqVJRlxl6BXxPQwodN+iRZTZCKBaFxWXnEp6q0UhHzJTDRiMv4MF0gUU2GDklJl4RLVWYmwmm12NnlGuXz1VW2b2+RmDv46xp4tFHS8eYskTf7VKz89c1dnLWYt/4LAAyrbDQ2yTVTMZ2Hjl9np2w8SRCCI7Uj3CyfxJN01haWtpukF9abNfmrzeUgj/5MfjkP+NZ8z7+5qnvp/aJZ5kstPmtbzX56e8t8H9/h+Ddby5z3y1L/OV9in+98xSfWn6Ak7WTgEfLeTO3H7+Z20+c4e6L66Smzide9zq8y2dIHIutXdfx1rTMb+4tsdy+zF3LV1BKIId3cVQ8yr/PvoU0WeSIEGhZSHH/mHYoKI+LjNJdKHOd16UJQrf4+MIUTfmUwgLdisGRieKEd5Ys1EBKZtWM64TPpumRhQZ1awldO8Xx0kG8fowQUDQiFkeSTKWUZrNrA3paFLDgTAm2Imauxrq2cs3BYhLuoqb7uIlPOU0IPI/FQt6MlcOI2Gvmk89fhGI9Z4NLKmRq2OiqwNQDFc2wpY6VJiS2h5EkeViIVyQN5j7EdoxPRAONiSqgRIiGjhcZjDOB8MAwhih0unIRNU/Tw3Doi5hmWkHLxiAkExQFngsLSaYGVUMxVQaeFoMSbIopYLIa9Elcgx4KQ+YDf0MrZ75D08SK544ZpsM0tfAr+RB1OTMx05wJ1wFHzENIgjqOHRHHee0OpnOpXjWml1q5i0X2RYzw8+DMZ0o8AizNwlFj1sIX0CDDtpPF8/DVNsh/A3ifEGJJCPEtwL8FvuWlW9YrG7/5u59i1QgpUOX9qynXqROIc/voLBSwZcqGc5HX2cdoFXys7/8AYve93PKjv07z+rMc2izTO7TOoeFbeOiAi3xIcvrbS+z+j0NGoxavWnqK5vj16FLn8ZVPYUwOMO6/gd+3amxoGm/gAgfMK9z54GeJlgP636eYTmsYGwnPTGz2RDqHq9+OEoJngozl+hk+tuxx3/QTGCH0zzZ40/lHOH73dWT1iIc738nMM6jHH+Qts4DTkwYaFbZKV9jVdqnsmRKv58XgXGEPbyk8SlOGfGzhXu6cdckwUNEyd776AFEW8eTWk9y5lBNgWZaxtrbGrl27vp5vFwBGsz4PCylgZjFhmPsDG84IKzIxpaRXqdELapTdlCwcArCuNViKu4S2iVRQ0AagFfOwEMsgG1jIYoflQLHhajCfcm5mBiotYyebjN0iqRkSWyWcsEcS5CzAgqZxwV7HTqssyy5ds4xvaSQit3pbYoNEM1lfXEaLwN0IEJrihjhnt6+4C+zaWGPm7ee8aWASs2dwHKEtM3Db6GZ+YZroIQqBNx1SVRNmcoHqMB8K2araCGVyRu38gkG904PTJFnC0tISm5ubyO3Bj5cK27X56437/zV8/ld5kG/lP59f5ttHf8B7XnM9Z1p/ndXJz/C68z/Hu479LO9+7Mf4jif/Mt/x8FHe8rkWr3rqKKvTH6KW/B+8+YNXuOXZE9x35hIqE3zkjW/CXTuPkimfu/vN/Fj7AT6w8C1segb3PvYJygcvoDrXEalPYYmU39Vux1IZq4FLUX6YlYJE9FOeiu8D4EFRZrG4QpJFHGudAqCc3ct1Y0lBCi5ZGwxEjBH5dEODFXfMiSxvqg7IG8jMi0xNj2iaQNlgcTaCQKBnEkNKus0WVhJSNCNsPSNsz5AlxTqLBFqEkTlkaYVSliF8H33uYFFw82G4xSDEbB58wdN7NW66QEygO1hpkXERVBDiKBM7SwjtAiJL8KKYmVci8fPWRrgxoUhoIOjJEqaeN5/lwGI0T9PDGQIwkItojsJKEpTpMiKlkVTQ5ACp1UmzBE3k65amRTauUNJgiElZzzdwhiInRvYEYyLXzMOn53kcQ01iaQ6xaWLMmWBhFZkmNn45X0M5FRjzBtnJbArGAFAMwwqOFzNNYsw4ZjrMSRa9EjGMXVASxl9eGuE4uUVqHG2yUlxBpF02ogT5/LAQpwpW8Sse5xsNX1WDrJR6GPg/gQ8D/xR4s1Jqm4f/M6LWfpxL6m7OFg+w5hV4tfw00RMH+fbyTZwPT3Ko+QgH04sY3/mrUNudP0kIXvvX/hnu8qPsP7uHC7tNbjt7Hb9xh87+6ToPX7cf63crxGGRHzzyfmrDd5DESzx28Ld5/OBvsGQ8ynfIz7HDWUP1Hmfc2iT6fonUdbbO7qP9uMEjhwfcs3Ynh50d/B4xSzLjkX3XkWnw1uoHWF8/zAPaft66dpzm7U+BDp8yXksxTtg/epaKlJyYXUffPQUC9s+KaHoBNbyInaQcq1/HrV7ugPDx2p1EvQEohcpcjh5u8lTnKWIZc8dirj/e3NwkSZKvu/4YwFycp+nZOUPrDXU0qTCdAYkqUUki+tUG08Cjak0Q8zS9K2aDYhYgTMVMNanoXXTKKCCwTNTYIPV6LAeSDUfg6A6ZFlPNdEAj8kPGjofSInynjhdsEfTzAYqmoThvdhDo7CVkvdBgadBjamSMEofVKJduXFzMi6OzlrMPe+igNOjoFXa118nMHdecLF6/eRrf2cHA3SS0878jmeB7i/jDIgfVBuvaKjZbaDKj01IYiceQKmydhDTm+vr1JDLh7Ogsy8vLxHHMYDB4md6pbyxs1+avMy7cj/r4T3NK3MvxXp/l4ZNcLv4Au5K/QTXax+L0cfb138uB9T9kR3uNhdnNLKY/wJHo7/KOk7v4f37zffzrX/x5vu3h49x7+gqZMvjIG9+AGm5C7HPutqN8f//zVNLv5Ff36Sx01rnX66LZPm77Ddzr/xHvT+9mkKxyd5JgSJ3k+k8BcPPmjM3wKJ7WY9qOMBdv5qlsiqY/jRRVYvdG7u7kLKKZaQSWwNOHhFsJK96YK3EVYUia8jBnSxHI+YBezWFh3CVM8wE9AXQWqujBhIoTkkmH1NexaikzCoys0dzBQlCWEYkfEll505s6ITIVLEYxzo5XveAp9rx8/sIT+U22HZUZeKDCFFdZWDJl6pUQMsGNE6ZeiTDMkNJAc2IiLbmWplfQhgBUfIvxPE0vsa6m6TUw3XnjqmlMlaKRVtGyAZmxhJNEDCwdU2kowyIZlnE1RU8zqM8dhTKZz5PsDgLk3OrNTvJrxsBUeEaZ2MrT9LRMkRolpqlFVMgb61KmIM6bbTd1Ma0hLinDuIJVTAhMA8/3GU9thFQY5YRpMJ9r+QrM79UGOQzXWS4sk0QbJErRjdPnHiREziIPL33Z43yj4cWS9P5ICPF+IcT7gf8f4AER8Bvz//eiEELoQojHhRAf+PMv939/xFHCUXWMmCbv36Fhqpj9ax06QqekBGPvfu5KT6Fu+S44+JYveK5h6Bz5gZ/nUOP9HBpOaHAbvlnm5DmDG9/8MI/LvcTvWSWJXf7hrb/BP1wccQsNvMIpeoffw5/e+D7+eOf72Zeepv6XUrKK4uLJWxk+NOPUzhlvGSxwe/3bOENGf6a4vv4Ev7+rwr29B2mlXfrHlzl65TTn99/MPvtpev3DnFyscsfkU7xtNGOAxVPeOzhXf5yir7NvcULvmbcSiR7lWcKuYo+pprhstNjhr3NOLlPIBHHJQNMEj7QfQSC4bTGfZL5w4QLA/xoM8nILJwwJr6bpDUDLFKYzJJZlqplPr9Yg8w2axghzEmOmMRfnYSGe5nNF7aWit9FFBQFEho4xUaROn+VQseEKikaB1JjgZfl23GxmMXYLIGBWaOKEPeLeLpSCmpmyrg8B2GWkjO0iyxubjB0IU8muWb49t76Q64qNztyD0xmiLJ1As1lpbyD1GpfN/HW9atwncHYQGyGXzJW5Bk4xKbSIhgYHVJezYgdxOaM27NBpZJhxFSkMJsqBzslrg3oneyevDeqtr39lG6Jt/M/ha1Gbt/HnRBKg/vBvE2hLPDqbEm3G6IUfpuxZ3Gqe4LWVmFuWb2fXjjdR3X0TzeZldqf/mkODn2Sl88dIYTAu7wHdQ5fQaS7wwTe8hniwgQp9No4e4XX6GvdO7+W3di+yWbC576FPUDt6FunX6GXnKWkBP6feAcpiv+Zih1sUj0y4Egh2jw268RE86zTfNuqhOWX+sFHAik4CNleaNe7p5PrjXX4NhKDUWGO5F+PqKX7fwKobaELw6WYNexiRAbJqcd1kg2G0RT2YR0zXymR+wII9IQ4WAIHR0lFCsOVuoMUNQFFLRthxxrhYQVcZswJkQwMBiC/TIOu6jqNZOCJnO4txmX7haty0i6UyRoV8t8uNImaFElHmQ1xGtyMCYpoItmSJopY3sNWZzWjeG8ZGLoEIsuq1uGkhIMwU9bSMmfRJjSXMZMKWLXAwkaZJMiliadDWdBa1vEHWs6tx0ynMG+Ry4CGkZGhqeHrpmpOFHSQkRoFU6ej6BGEVcNIUPxagFG7mgjHCI2WYFDHKCYFl5GEh2TwspJAQXw0LGX75+2LLWkAInTBcZ6W4wiy4AMDaFw/q1fbk7ivbAF6cQf5XwM8/7+cHgX/8vH9/Nfhh4OSfdYGvNPzB+55gv9XDo8xHljRu4xGyU7dyZ+MIa9klrnceRrM8xJt/6gWfv2epweW7/xrXizHTlQvceulufus+ndp7wfueDR6aHiT5zzsYDZfYVdnkryy1+ZmdE/5uM+RHk5B/5ces/MWE2DW5cOxepk+NmLops10Bb579VTRh8itpyJ5Chw/tuYdYU3xH7b+wubmfB5ODvOvsZ1j/CxlJWfGJ8XeR6YKV8D3cG4Qc7y9h0uBK5RR7NgrUDgwYn6+RadAxF/lW935K4Zg/ab2OvzR9nDWWEOEyzcO5V+/Dmw9zqHaIip1LCM6fP0+z2aRcLr9s78+Xg7mcM8iBkzeSC0MNUoXmTAlUlboc0q/U0APJguhT8HVK0ZQrbv7aSky5xB6q2hZCKyIQIARWEJM4PZYCSWBoaHYdofcx5l7InckisZU3trNiDSOL0Pp10tSiZEWMyAvzopE/vrrVZ1DQIBEs+SUcFbBZa+aDgbGGjBycwgDl6oDAjCI0JembLWIBB5IJmZVr0c6LMg07P/7ELUKQcn22yQwX3RQsdDdZL+pYca4fX2cR1p9gZ2knBbPAid4JFhYWMAzjWhriNr5m+FrU5m38eXD/v0EMLvB76SqT0zZG6fu5sTTkdfVbWXGPYKoOMjyOHq2xYC1zuPod3Ljw4xRaf4VB3War9Fk6zdM8cWiJjx69i0d2tDA6VxCiSPO6Rb5HPMUbu6/lrHOYX99nc/DcCe7xUuzKJtbam3nT6L/x4fQ2NmiyNx3RnDpU3f9Bw1HonZTj8WtJlcPDusMhu4JSkodWriBUTDU6QGJr3DBRPF48STrLm7KgGXNDEjLUTKK+SbHYRGoX+UTtJhY38xtuSjpH+xPGSZf6eEyimwSuix7O2OsMCIcuiWGSVfLGre/2SKMVasYEK5pSCiPGlTJ1JmQlMCbz87l045c91Z7hYOnz/05KuRfyDIq4OFnKqJRrcovhlJlbZCZ99LiMZYUEIsYRgp6sUNO6KKUoRUXG8xqbmrkEMJVF7Hmani4TkjRFR6ceTpHWAlraZ9PTKCgnZ5CnNjqwZug08UEozDjfOVwNxbU0PTOtUpmNGDkOtl5gZmoIoDYckej5i6oECuXWsKKESWJjKoWbumTGBBvJOPPQqpJEz8NCJnoBM9NwvJQgmjfIX4FB1jQD21okjPIG2Q8uArD+xYN6tb0wuJDr6rfxog3yp5VSn/pyPwBCvICqfg4hxA7gLwC//jVc8//W2Hry82ypmzlVPsTYdLk1eozRlRLXiyKBeT+H6aC95u9BsfVlj/GOt72Ni7UJe9ZbSKdGfVzj/TWDu888zRNv289Hikdp/KbOuSfvJIoKmBrsdyW79kmS6wRr60dYe/w1hOfWSAPFU0dH/OjFv0PTWuJnCNibGdxWOct7dpV5ffdTLNKm/9gqrzr/FJd33c6r3Q+TzIp8qnEdBycjjnbXUMBTk6O0S8dRmuLQuIxZFIjuGTQpeaxxI2+wnsRE8aet17Bz2EOhYUQLvOa+ffiJz2Nbj3Hvyr1Arj++ePEie/fufXnemBeBUS9gKYPAyYcFm1MXmYBmBcyyKvWsR69UxgojTJXhRSaVaMCGl7+PZTVlUzWpaF8YFuImIVL3WZxPNQduE5c2SAOUoh/WsY35FmAxvwhYPRspdRxnSpaaKJGyIOZWb4Mpg5KOQKD5KyyzxrBYIizYKEugBgXMUpd5/giXFhZZ6W6R6CtcNk0WjAGpkbO+V4yEJeeqdVJeKg6PzgCgIpOF3iZjq0Qi5taC7ID1x9GExg2NG3iq+xS6rrOysnLNrm8bXzP8uWrzNv6cGF1B3f//8ofiZkrPhMjWu7i3YrKrcIQ4+wA7ne/hcOX/4nDjZznY+Encwj/nrPnH9NLTrHj7eP3yu3nTjh9mx8JbcSt1Ks4au0oT7tox5gcPPM47M43G6EeYspu/d72OliW89eFncG/5PCosE4TncYj48ex7UFmBuzQHVEZ855MEEl6zPqET3ogpZmz2UuyV2zgTDwhKz6DQccQbuHmYYSnBeWuNgZZgxD6dQGeHO+Y4i4Bgn7gOTzzL6eJe7EGMZgma6ZTCSEOhKM+mjMt1BKBFAcvuhKAjmbgGXWMRBYzNMX6wm4YxwU4DynMHi5a9geEo7DAl0ow8ye3LwLNdjHlQlBU5DAsCkQm8JMWUGdN53HTRH6E0jY6RYUYVXGNKJiQJGVOaLGgDEpXgJlV8mafpJdfS9IoU3ZwQMNKAOMtdfBbCKHf3kRt0bI2yLKBM61qa3pYlMFVuueaGM2ItYCG2rqXpqaRKadpjWCznaXpm/rWsDPsket6IlkKDzCliRAGz1MaVEi8tEJrB/8feeYdJclVn/3crV3XumZ68M5ujVjkgCQmEIjkaZIIx2OBs7M8B+8Ppc7bBBiecsMFEg7FNziCBctZqpc158vR0DpXrfn9Uawk2uxgFg9j3efqZ3Z7qqju3uk6dOvc974tOTFeahAUdhMCJQlzdRot1HCsmlgquYkDr1NSIVOptkYnsBGqcVtLnvlULubwewh50V77jS+GpjNMlyDcJIX5OCPFNa9xCCEMI8SwhxL8Arz3F598B/CpwpkNngPXBftpyhs+PJ+gyYPK4hz5UopV0qQQ3k9gluPiNp9yHpasUrv8VtuX2U8od4ZyFS/j0xQL5OZU3Tf4NX9r0NKrn5nn+I/cjPnoJxz53PQfuvoqH7rmOO+55GY2VYRpHjhHUdY6frfH7S79CRVvLnwgPJRA8d/x9/PHmG7CDPi8bej/Lcxt4oLOeZx+/jy+/bAOy5HP7ymuo5zUucT/A89o9HknKLBeu4cDQ3RQ7OpvGu9T2XU+QLFHq+mSHVaRt0xUWc/oQcx0VTSb4mGxdW+SepXuIkojLJ1Mnpfn5ecIw/J5JkJWMjmrm8A0FiSDv2gQRCEUS6hplt0HHtlCiIHXTi3XyYY2lbCpKX05a1MiSU1cR4utmIYkKUUNnOEw5aD2zhJ00EFKlKDy6YZaSUSMWCp18mlib3S5SCmy7gwhzBNYqZSW9QShuRL2YLuHFvQoTzNN0snQyORAJalXByK0wFqeB8cDQNOsWZnGN9RzWNDLKKmrcR0+y1Oxl8oOyTdNM1yMn28fScUcVSs1UnWKloKMkBgflNOGJewDYObyTA/UDeJHH5OQki4uLRNE38N3O4LHiscbmM3gsuOXPieIYJ2hSG342l2VKFIwR4vZfMnvwAf5h4Zf5zebf8rvtv+UDrT9jufPjbA4mKVlzfLZ8hM+N7KFl+czkruTS0Tdy1fj/5WnDP8u08X/p+++kHb2GedHl/6wTHB/OcP0tX2F8nUu+tIRfvZDr6p/nH6LnUhUFRlhkvFtgvPU1ytMhh9oKJc9hxd+JaRzlxc0qijPMhwsZjGA3UinSKKzlikWfmJhKaOMaChm9gTsfMZ1pctivIBTJmvg8ljNNYkWl3Q+JigYj7Qaxx8kGvWplBDPwyGgDasZ8lygHx8UkITEJ0PGmKAoPK+iTkzGu4zBmp5SAou/hZ0f+WwWLR2EbOmKwSiZ8ndaAdmsHTQDCQXNz9pvspotktK/bTfeUCqOigSti7KiCRNCLBEIfuOnFOXJmj0QIzKCPDOoAVLyYWB1CyiVWLEFOWkhVI/DSY/YHC5yqHWP2PXq6Ry7KIoREVyCIMlhejVq+gKIZeAM1i0K7QaBESMByNTzbQnHT8dqxjxNm6KsuqoiRKMxFoziGxErSOCqTPJYhQUha8juTevO8BSYyE4iki6NITrjfmiAP7reNMzQLOH2CfAMQAx8SQiwIIfYIIY6SOjb9MPAOKeV7/rsPCiGeB6xIKe871QGEEG8UQtwrhLi3Wq3+z/+C7yPMzrc4W5sjIwxuHtPYyS7ifWfzbGMdDeM+zsouoVz6M2DmTruv51+0mbtKkwyvTBE6gvULQ/z95SqjH4v4P+f9Ne+wX055cpXizAEm5FU8v/laXlB/OU/rjjN9YJJN6iXs3PJcfr35S6hJiV8VLkeihHOmb+O+7A9xf1nnpe2PkJU9Fm9fw40PfYE9W57Oi7PvQ/oaX8pcTsmP2Nn4PENJwsNz02giw3LhOOsWMgxtXaF9eIZQTWgqQzzHuAn8HjeVLuaHardwmBmsIEM8bCCE4Nb5W7E1+6T+8dGj6QW6du3aJ/KUfMdQbA1h5VHwCPUMGV+jO4gtqtWm0EsDWzvjkIQCJ9HJxMu4ToaeyDAW1FgxsmTVVfgGNz3X0AiXLMpx+t2vWjqDogLjpFrII9ocbStDO5fSOxy3ShLr6HpAXlqsOLNkRZFy1KSfGCyX0+28zhjjLNAxs6yWhlB8ibnooTurrOullZLD2SnWz52gnd3MMV3Hkh3GantAnaLmLCCNVJfUFx0CPYvsqqyRKzSYwIpTXnF1VKIOGvWU6l4I+uys7CSSEfvq+5iamiKOY5aXl5/Yk/SDhe86Np/BY0RrDnn/e/m0vYX9y9dwrlKibE7gNe7ni+t/mr/44T/gra94Fv/4wu383fO28eZrtvGinTO83oQvzjfYfLzLRfM5FmXEu4fn+cexVb5Y6nO/DXuVBndoB/gKt/COSZu7NpW5+ME72dodY3T7V8Ad4rz5rzCXDPP2+EWQWFwV22iJQN/+SXQFxhZd9gSX4ckCNyk5zraKxEnIV9b4aOEsdpBnsWxwcT1mv32M6XYZFIXs0AKTqwE5PaDTNNCHFHRhcVdZAzeilUjissVUZwk36jHkSQSwPFZC7bcoWC5xYhN2wCyG1CnT0Ttk/GEkOvk4RvZ7JOag6W6gHjHl9jFGd5xyyk1LEqoCNYmIAoPWo3bTA0toddDAl+2l+6xZKqZXIqN0ESLGxSfURqjQpKOAmaSFi1YMihmTUWr4SZ6i6OJZFkbQRfTTAsCIr5BoRUIxx8o3aCH7gya/JJv+1M0ErRtRN2MSOYwTtNEMhV5ioUV1qsUhpKbhPuqm103NQoSmQWDQzuiIyEONE8y4j52Y9FUfRaQJ8UJ3jJzuow4UgeIwj1BAtyPqsXpKDjKkCbLvLzGeGU0pHorPsW9NkEuDBLl+5JT7+kHB6YxCPCnlO6WUlwMzwNXAeVLKGSnlG6SUD5zi45cDLxBCHAP+FXiWEOL9/80x/kFKeaGU8sJK5dvTCp4K+MAHvgDKEHOZ9dT0HDvdh2n2TBwEauOLSN2Gi97wHe1LVQTT1/0U64cOMGbMc9bi2Ty0VmHhuMqO44c4/9yH+IB6HZcp9/JpYx+fbfwHy71DbIm3cXH5Bi4qXcNGdztfCQNeprjMItkytYdzwyx/tmWS8xZ3c3Xl09R2r0NbiBkNAr708g3oxTb3zd7IkVGb57Tu4OrVDvs1hxPi6Rwrpc9Cm90iim4jqocQUrKrtJ1rjfuxZcy/j1/H9f3jtMmDN8nac1O+6+0Lt3PR2EUYarr2f/ToUcbGxk52MP9vQygCJVPE9Fupm54P9SgNjJrVptBJGz0eddOzFQM7XgJFUFeGGPOrNE0TXQQINVWMeNQsJKyaOMYSdpSwaCkkpFXbiUSQhGUKyTGaTobQDAk0B9utEnlpkj2uqhyxTmAlZUZljVWjQNcWxMRU+2NMkHJ/j05Oo4QCa85Lpd6iZSQwZ46wdnGOyJjmqK6jILlm/ggdZ4a6s0THmAEk4NPNjNNv2GxJFjmmTEHWxel3WR0O0f0iUqi0yMLiLs4ePhuAh6oPnTR5OUOzePzwGGPzGTwW3P7XHJBlwsNZpuwM05mdrCoub7nmCn7zwiH2DXW5LLmZH3Y/w8vaD3J21CWYLvDAVVfwWz/8Wt5y7jj/JO/kxPHPcP6Bg1x/tMVUqwn+IsSLRH2f927dzk07Jjhn724uPZIjv/MzOJkWmQXJiF/nx8JfJsRkTN3LiDdGsfsQyiUdHukrPHu1S807G0N0UKvLmOPnsidoEJT2A+BwHUOBZKMruCfzCG0XkAn1cszZskdX0fBrOtncEKEyxxeGtjC8lMa3pGxyUXuemr/IUHeg0TtUJu71GLfaBG5KzbCGU4vpFWcJw08blctJh9iL6AzMKjzbJ/YVimGMte6Zp5xy3fSJVMjGXbpxSrEAMKP0odsOfKTQyPQGdtOWhuanvRGG4dIXAQVhkJMRDU3FSFJVh4YUaJmQrFrDS0okQknd9Lw+WmeVmIThQEdiEYg5VkzlpBZykHZ2YNjpWCwjRPYki4YklsPkwjrSUlKnu6SBZ1knzUJ8VcXy0jm1LINuaNItpslqPlIwo3bap4JEH7jpLfdGcIweycDn2nfTQppS8qmFRlpBPgV32LImkTIkr0g0oZGhw4kBte8kitMglDONegNop9tgwGO7GHiUIDQvhLhbylOzuKWUv07aXY0Q4pnAL0spX/2YRvt9juLqAeb1zXx+wkCRMTMn2mSLk6yIJXZmHkE5+5VgF7/j/T3v3Bn+6HNbmDmWsFTqs2W2zJ+8sMZffzjhRf/nP/nwlh/hFXu/wnOUr/F/y2+kGLQZCtucQ4aVOOI2M6GhCwoFjSu0W3iFH/Cas28k73Z4ffGv8Vo55u4Z53mH7uATz/oxXm79M4mr8ancDWSCmAs7f8VUFPO+xgxx9gIeGftzxlZNNq2tsbL7+fjxLop9n+JZNoYu6MUm9ztbaFRTQRPNL/GMp08z257lROcEr9r2KgDCMGR2dpaLL/7vu5r/t6DkSmR7VXwjj+PXWQoV1gGq2TnpplcbuOllLR3kavqeKDMW1OhZOrigay6uoqPEAa6uYdZU5OQq455kyRbEavrcWolVZJRHCau07CyxuoxnlbDdFZY6o+SH5hlR4YiyyDPiHGO0eCCzicnqMj3NoBkZTPbrkIHj4+kNwVhKL9uKWQe5nobMsW5hFqkWmTXSZo/LWg0+ZG7H6oUcVkfIaofpRhYdp0hpSbI1XuLL6k42ZUNGaovMl4uYQZk+x5hjjPL8vVRmLmUsM8bu1d28ZvtryGazZxr1Hmd8t7H5DB4D/C7J/e/j6NAIC9FmnuNezpIZ8hOXGSzpCq+W7+aZypdYVCbR9YBJcx5FJMjWRt5Tfx23W9McW7+FY5u34bh9Nh95mLGVI1i+i2dlmV0zzf71O5BC4Vn37GP7ko42fTtr1z6E1shwyfwB3uT/FAcZR6g9ro7GsELBxMgHSHRw52Jq8Qxz3vm0zQVe1a2jTOV5v21ghPeTiCz93HlcO58mRh2tCbqGGQasNGE60+IBJkEK1ovNZMWD7Mo9l+IRn74KeeEyU5fsj7sMNRu4lkNgmmTcLhvLNbzGJJGaEA+nVdaqvULcPgdL8cn7zdRBb6hCNnHpZRVoqQiANZeccto1owlAQfZoJw7eoIKshVVgiqzvIVWHbDdtkmvZJqqXxjPD7NPteAxRxJGStirQxChi4KYncjG2UsdLCrRknsjRcTp99CSiIQKGogKKdJH0aGjypN10pCrEgaCoS9xEJaOGrIYK82qIpMKYe5SDTpGVpseESJPh+sBq2jUMMo+ahZgO7b6JLKdjLyY68UALWZMKzuCzq+4wlh3Q9XoocUyvkcFYA0rZpdGwwFyF3uq37V9y7FQyNvDnGMuMEcRVDnkjJFKiPEpv0YxU6u0MxQI4vczbdaRLdr9DKj7/HOD/AQcHvzuD7xBSSnYmB3BQuXlMYRuPIA5u4hnqCLG4hawTwsXfWfX4UWiqwoZnvZaN5SNMsMD2la30bIVPbtEov1flZZX385GRq3mOejcX6Ac4po9xn2nwz2bIpxxJYLhsLp7gd4K/5wXS4vU7b8RTIn7K/wuKeh33Y8M858G7WBw7l7lnt9DzXW6bfR0Hx2xeVX2Iq5ZWOaibVKtb6ViL9MwWmxaKlLau0D08TKgmNNQKL7c/RxyHfKF8GS+rfon9ci12pNC1NCaHHG6ZvwXgJP/4+PHjxHHM+vXrH/fz8FigFstkex08M4/lu8zLb7SbTnOSWqFIzc1T1FW8pAnAkjrEmL+KZ2pIwFHqSDVDIsAbmIVETo0xV7JoKWiqRayEFAZayJ0uA6k3STdbwemv4NUmkRLKRsgJNeXKrSGiaeUYX1qmZYIXJ0x3VYRMWKikmsbKQOotk60jTZVAqIw0qqhxxJw+RgJslC0iI9WePqKqjFkD+oiTam+e1T+SNlh2BSOri6zYJYgzgGC/XE8yey+Q8pB3r+4+aRV+poL8+OFMbP5fwq4PcV8yzsGjW7iwuZEwAz95hc+qbvFmfo98P6C56xlcdmeb6++cZfIBB3d5AnJHeN3at/Ar5ru57mNfxbx/lbAJu7dcyOeuegkfu+FVfO6ZL+Tw2h2cdazNj3+pxgX1BmLofs7ffhNalHDx3jn+rP0SPiGfDqhcHN3NcHeCUu9uvGvrHPQUbljpUPXOJsbky+RZV16PG3a5dRoM7xH0uMj8kMOVKyHLWo3NvQKhaZLPLpKc8FnjNDkYDCMUyXR8IX3zBE0zT78dEJdNJto1ZDttIM56HvXyCHoUo8U+41aH/nJI2zFYHjT6No0mPXeGUaOB4fco9H0apRIjag2Rl2idwbPcyNZTz7ue0rkKSZ+uYtK1bRJFIsMmagJ26BPpGXTfxwxCek6OpJ8m6brh0hUeQwj8xMATIQKFjKcP3PQkupZSNarxJNJWsPsu0szQEFGaIMcNpMjgygRLpquciWYQtbKUtZQDnFPTRLY6MAvZ0GvhOzodwBh0YTXUCFOx8Q0D9VGzED1HJzRx87XB3yhQgjRBdmIbS29hEVL3ShjZkL4Ap9en0XBAStRSQNsdPDE0j3/bKbTttF2h7x5nMjtJ5M/hJ5Kl/yL1tu5MBXmA01WQ/4JUeP7YN74phFgHfAbY9p0cREp5M3Dz/3x4Tx3cdPsRNhk+R80xFswSV3ifpdlfA7pEW7yT5OmXoIzt/B/v9yUXruNtX1zD5HGFZCRk2/ES/3ZRnWfcLCh+JkHccC8LjSH+r/ZB9mw6n4kTc9jtLo/IUaaSJr8Q7ue+0TfwfzaMoUU+P1b/R7aNPkjyiSKbH1rFN0q89Udeza+qv0B7tcynhq4m78U8q/uHjEUx74u3kRSewe6xz2H5CmdZebzGJpT6Q6gkPFA5h1/ksyhS8h9j1/Lr9a/yEbaTcdeQ2VQG4CuzX2FdYR0z+fQJ98CBA2ia9j3DP34UWnkIa9nDt4ax/R4LUgUZolktMn0HRUrqhRKrx8sU7Iho4KY3pw5xTb+GZxh05DAFtcqKyJOIBq6hkW1LQrvGeC/hkYKGo2aoah2cOK2ArHaHcAvppdrJVphYehBWK8SxTt70WY1TlYuxQaNKsdqgmZlhsirIuxMMs8pKsUyiAEIjbpsY+RWUUIGeYHWkyJrqEl19HQvaAwxTJdaGEVJh0WgxbHkc6n7dcnpT+yAUwfKGKbJArGjU8ip6bHFUmSKa/SwGcPbw2Xzx+BepuTWmpqbYv38//X7/e4Y2832OxyU2n8H/AFIS3fFOVsYVCu0xJvJb+LnLa8wr23mTfBtDuzfyupVbcfQV/EaHsK0RleAKt0rmUJ8HtpbZPPQVpp6/i8qtS+zeP8P+oRk2Gi7PFfPMhE3W+POoehVp1bH0gP7OFXxDMr5H521LN/JP2ecCkC18ni2d69HimDXTHyQwYc8JwQv8Are5l6MoDa5ZfBh9/TV8yl+B8hKiGZPl2TQknNORfLb4EJmqA1nQJqqcdTTEnIzpLeoYFRVNmNwyZIMb0Y4ToiGLifZB3MAjGwoUYGm0guF1KFg+miLpzXUIS1mOimkCYiIlpuvNsM6exQ77lEOPPfkcO+3dKJok4wb0jQzOKfpupJQk6iFghHziclQzUESOntMl732D3bSRwe63cfyArpMjmk0TUM0O6IuAIRQaSQ5d6QAOeVenPXDTk2YTgHoyjnBWUjc91aIjk4FZSG1gFhLQ0XVUKZC6Ttwqki13aCgapYFZiCfTRHdjv0dSSuO246cJbFNLqHyDWYiIJZFewItMTOcEoOGEklU/QEpJJsqg6k0cL6IR5NFyEa6hk+n3aFkGa0KJkQ/xesV0supHYOrC/3YeTXMcIXRc9wRTuSkeWDoExnUc9wImBupMQNqot+fj/7Nr4ymK0zXpacB/V/aZB/THfzhPXdz9ha+wKtZy+0jKx5qer7EmN8mKPsdZlYMoF7zuu9qvpavkL/kRNpYXGI/n2bK6ES0W/NNGDXVJkLsDlraEbHDneJX7cW677CLuu+IC7AsLrF6ymdc/7TX8+ZZxKq1lfq7xDi4evRnjZoOhOxLUAD78/DfymuE/IzYSPrr668wN6/zi4te4cKXKnZaNPLSGyMgwW9rLxrksa84+RPWhF+CyTL4fsWNt6tbXUhwesDfRXU6Dh+FVuPQZM7T8Fvcu3cuz1jwLSIPhwYMHWbduHbr+vfUVUysj2K6LZzkoMoGOipKAYa0SJ1kKUUCtOEyvb1My2ohODyWJmTWH0UgwNJ+lZIaStohKEYBAVTE6yUmzkJahYBhF0FZRB8F7uTuBrqXBt5tLW6aNqkUca9hWhyC9DzCuDIJxs0s9r6FIBdEdZ5w5mpks/YyDVBPEqoWRX6JM+sE9o2tZtzBLz9rCYV3HVFfIdk9gyjFqmQVMPQ3ubbVPIlQyvR5FOvSTCeworeysjiWoQYY+GUR3Ebor7KykD3y7V3ef5CGfoVk8bjgTm59snLiTw22XB+bOYWd4Hh++8C7u1c/iJfIjXP3gVq5cegGt5G0s+u/lmP5PfMF6Ax+orudLt27mbzOvYP2BiK37umS0VZ591b9z9XV38OrDn2PB1fl7bx3/KXO49hFmjIdYWzxA5/xlXFtwV/Na/mDfj55MjvWhL/HixnpG6zYbWh/EfWaPe3sqL11u0QqmWQk3c4uh8TzFRMqYfx4vYvr3ITHo5S7iqnkPQyocs2ZZxUeJQ47GJluNDsuqRdDUKeTGiZUjfGr4HPIrA/5xyeTC3gnq/gLDA0rZ6kiJpNdi2OoSRgXivopRDqlRpq13cLwhEmmQjyNEr4uimUihUMyk3OER10U8qpzwbRAEKwg9lR3LiYC+akGSo5P5RrvpiL6dRcQBtp9WkH0vIU40FNvHEwHlgd20o6TV4kLPpPWom545kNKMyqhW+rcpgJtIhqICalwn1sYxgh7LtoKJnmoht3JYAqqqxoiSrrSpUUqtW+9GJ6Xe8m4WkaSURkdLzUIEkO32CVUbiSAThQirgBlGdEMDDYkTOUi9hUVCO3JQixGerpLp9mgrGfRI4GRCur6dMqJP0VynKBqWNYnbP85MfgbXPQzAcfdbeMjDm8FtpHSNH3CcLkH+Z+AeIcSbhRCvHLzeDNwF/NMTP7ynDia6R3HlKF+dCBiRS9j7x3i6OgzR1xB5E7Y9/7ve942XbeQmq4yorkOWhtl+rMQDawT7d2pE+xyCBywWRk1+ZuFD/P6X38r62gqelcXXVbaszPOjuz7L7/i/xo6xe3C+rJD7tI7RSbj5ytfiX7qX0exxvnz4xdy6fi1baj7Xt/4ETcKH4q2omct4aOLLCCnZ3J/CyAnC2RaxCifMaV4jPoBIYj46eh2vXPoc+5M1GLGgrahctLXC1+a+Rixjrp6+GoBarUaj0WDz5s2P19Q/btDGHjULSZfuhmoCJZYYTp1A5ihFPWqlYZKeyojSINMTZPwes2aqBJERfY6zjqKyhFByKDI1C7E9l8hsMDZwpfLsCllWINFRCWn6RfJGgwRBJ5cmq0Yr3da2OxA5JKpLZdD8Jz3JajH9d9wZY4IFmnaOdiaXjnchwswtsWbAgdtTWM/62RO0c9s4bOhk4xZrF/fjG6mShW+ly6WSTtqo18ywNZlnTplCt5poYUB1xMf0h0AIFhmFuXvZPrQdVag8VH2IiYmUA30mQX7ccCY2P8mIH3g/uwojbGgW8bYc5+8K17NeHuRHj/iUl69gX+sBbl/5BPc17iRI4NLidTy78kZWhidY3rfCz2Z+hV3xhVz0QBMzSLiwdBuXvfEr/P7MW7mx/AnkSIePTp7FJ85dxyPnOBzXxvnD2V/lI7c/g68VzgYSzLGP8sNzCUO9s1HiOZxrbsEDHqoKNrgFFtxLEQTk60fITl3EHm+F6oyC4e1CZYbFIZvrFgO6Sp8tgU3P0shodXonXNZna9yVpMnq9uQCCuIB7iueR3nZR1Ehq3psqIf0ohZDrQaxUGgVCohel2m7id9NlSEyozGJUFjKzGP5KR+2HPWIXZ/uoEFP2n2SSDDtuVhrLj3lvHe7B9D11H7ZISQRKlqcT81C3BgbAyMJ6Qzspq0gSBPkuE8cFNGs1CykIgXVJEteTRWDin2L9kB50jXSJNFLiphO+qZKTBAn5OMsVtAk1kdRoybztoIjTRLdIOg46ALmNJVJeghFYgQtJJI1rjjppqeFJQrdBm3LxlBsegMt5GKjSTjoOSm6KrGdR/d8OpGJHSc4oUOkd9BJ6EiLuKySKApO6ONqNnpskLFTLeSeYp1WfcJxZnDdE0znp1GiGgpw/FuVLCpb0p/V/afc1w8CTqdi8UfAqwABXDp4CeBVg9+dwXeAOI45WyxiKQaPZEc4K9pNoz2MKsFcuh+x7XlgZk+/o2+DkZxFb/uNbCi2GfHn2dRYj+UrfFio9F7pMdfcweLtBTxD4VWZz/CW8Ff5m3t/nL+55438Zu+XuPbsd2EVOuTfq1L4dw1Ch68968f52vMVnm/+G/uWN/LFwsuJVMHbF/+U9S2XfyiUmNgzTmxNs2/kLjbMZ9i5dZnVh1+A7N2DFYS0Np3DeDyHiuT9Ey/gNcEBjjCN6k4i1+RRFcFXTnyFEXuEHcOpzM/BgwcB2LRp0+My948njPG0guwOROknagIRSVS7iS/zlGWLeqGE7saMBnVyrkbBb7GQSa2e83RZkBWK6gpC+fqSoh17RHFMxU8rEH2zRDZaQUiVYcWjF+QZ15boGTadXHpsp79KkqjoekBW2jSdeXJannLUpIPN0nDaSNLojTPOAqGqMzs+hfAl9lwfRfc5y68hgSPWJGsX54j1cY7pBiqSq5dX6GTW0TObLKkz32w53dDYEi9yUKyhnQuo1JeZy0YnHfWOM4Gcvw9bs9lU2sTu1d1YlkWlUjnDQ36ccCY2P8kIXVYf+Sx7uhvY7GzmrZvL+Jj8RO/jKPuu5jOz/8C9nVt5T2acXyxu5eW6wr8EbXLGCNdO/Bjr3TIbd3+etxnP588rb+SS+5oUGwqW4lHessKzLryJN579Xl62+ZPYWp8P738Rv3vzL3P4wCR1s4CitilN/zGvPGyTES9EEnDOyJ8Qr5P8e9PgDdUmIrI44F7JLkPyhsBDaBZ/nMuhOrsRMsBUX4IdJlzSglvy95NZziE1nez4HONLEeN2l4VODtVJGEm2UneO0dJzdAf846lWDaWZxp/hdotmcRgFBcV32eDU6a8aeKZJWExXuVbtKok7jSFCin6dvBvQLJbQZUQ7K4ibGpoEseHqU059t7sXVY1QEFiPyrmFGerO1+2mdZnaVwM4gUvXyeLGPRS/iGH26QmfglCoJgWGlBWkTMj6OVoDN71ATTBEjyjOY9tpxVyLfcI4TcwrnkesjyLiZZZshdLALCTo6igCTpgCPZFomYhMv0Og9hkJzJMV5DjKk+nXaeTyaKpJXx8kxc06gTr4mzyNwM6gel1iqZBJApwoS1froZCQoLBIBUuXWHJAao5SLWShJNSkftoE2ban6bvHWZNdgyCmrEYc/1azkMqAD17dd8p9/SDgdBVkpJR7pJR/DPw28NtSyj+WUu554of21MFHP3U3tm6xrzhJIAzW1eYZzVVY1ZfYWjmEevaNj/kYr75iGw/YCvHSOLI4wQX7hzk6Cg/cbVJ86W7ef9HP89X952F6CdtX2ngXxriXJiQ65D6hMvI7Os7dBvMTT+djP/TT3H6Dx0/of8lsZ5IPdt7M3KjBb+29k531L3G3ZXJbfxOmdQW7Jm4mUWLWNmfITVVpHdhAX/eJwwyv3HiUSCjstteT9H0WVjpIFCxvlHOeNokXedy2cBtXTV+FItKv4oEDB6hUKhSLxcc8J4839IkKlufjOilfa7RtIU/aTZcoJnVq+TxW38WSAU5gUPDrLGbSKkoxaVMjS16pfpMWcqQJgqpFOUrpJw3LRhmIwU8mEIdFhtRjNJ0sgRUTqha2WyX2Uy7vuKJy1D6KLcuMyiqLdplI8YlJWA5zTIRLAByZXIOQAmMxDa5r1CoosKyVWbcwC0JlwUhvbhf220RG2tRxQM0xPFiCbDs5CBJ2ukfwMdD7AZXaEot2GZEYKOjsk+vxjt0FpI16D68+TCITpqammJub44zIwuODM7H5ScT+z/D5eDvrakPMnv0gd4lLeTpfZdsDV/K1hffQUkOq3gwv2H8Xv/XIP3Lj4kf4bHyMH6ePJzSeOf4aZsIxnnn7J/iUGOOn1/8W5zzcYfqYRFFiuu0pPjL7C+z90NMp/p5J/7YyTt/Dli3WGB/hRZ0/4dknXoyl/BB6FHOR/E3cqz1u76jotYiZfpkj/auJUfH7JxiZOI/jvXkOrc9g9W4lwaQ6vI3nHuthSoX9mb0sRD7IhBO25EK6BAi8ZQ17OEukdPnKUBnRjejGCdGIzUzrOJ4XYMagSsnixBiW1yWrp9rJvdk+nYzCMXUayaBBr7+BEaOZNui5PvWhMmNqjaQAemsQB6YuOOXUd7p70YwKCgJtYDdd9LLUB3bTGWmiI2lk09W1nNsh1nRqSojhF3G0LpGICYhoM8So0iSQIXaUuuklCcQqZNUaYZIjZ6exTg96RFHacDfiRiRahYR5lmxBXjpITSfop/etziCca3aM1XVp6z5mUsKMXXRN4EcZzKBGrVACXccdmIXk282TZiGap9PNWgi3hZASK+5jxxYd1UOItJFurjtO3vBRBt5rUVhECDByIdVQ+w4S5BniuMu4lQ44J7oc+1aKRX4SjOyZCjKnV7GYFkL8qxBihXTp7m4hxMrgvbVPygifAjh4724WlXXcNAWaDBk/DFepa0iSO0mGy7D+mY/5GDunCjwy9XzWFaEULDDlb2C4YfCpUcnh2TGu3fZ3vPWlv8dvTP8sxSBky12SD3/sVfzEw3/KH3m/zoe3/QKffPab+KcffjrO5s/yOufvONRex7tO/CKHN5V56YGjvKb9m7QUhf9XmuKCR6bxM6M8PH4z6+cdzl4X0zhwLVrja4hEcnD8Ai5ceh+aTPiXqRfzs40vsJst6JFKT5pcf+kabp67GTdyuXbmWgD6/T7Hjh1jy5Ytj3k+ngioBRtdz9C3UvpCsWcThKAYAR4OBa9B07HRQxeZgB2bZKMq1ewQMQrDcZOWYpBVa99UQfZ0jWDZpqAsoyWSRUvgK+kxxhOVJCxjhvO0nAyR6uJZRWy3ijtY0qxoksPWHFY0REXWmctWmFhZpqtFtJOEmYFe6exA6k1bTpf3cpka0lDoCpOJ1hJ6GHJcT5PiGa1+MkE+roWM26kEUXOg+bmldQCAQqdMoT2Lp2doZyVaZLPECOrCA5Ak7BzeSTfscqx1jKmpKTzPo1arPXEn6QcEZ2Lzk4vO7e/kcKHAxsIwf125HEHCa5Yf4Y4Dd5AkHltbIRsrfZrnr6W6dRPrFJXf3vNvPL36Dn4pXqQrBFeNvZpKPMrzbvo8d1HjNRv+gLXHJWc97JKxl3lJ5V142y7gPT/ymzibS7w4uodXte/lAuUSosqfM9k8HzXuc5H+a/gvq3Owq/CfDZ2frAUMJx4P96/nET3mTV4XdJvfczLE4x6GvxdDuRbXVLlmRdJQ2+xwM3QdnazaoHncY0O2zt3qGpJAZa2xFUO9l88MXUx+Ma2gyrLBZf5Rqt4cI2n+yNJ4BTo1hpwecWLgrXgopZgjcgZPBKixSSOYoKJ0cMI+5dClWSwyZR1B1SWOF+DqNgzcRr8dut29+NoIQkiUgZte3nNoZQQiEmQjH1VKPDMtXOT6TQCWzQTTLZLV2oCkL3w6osKIaNAXMXaYuul1I4HUYrLKKmGcp6y18Q0D0+8i3JSOMeJDrJaImGfJUsgOzELcgRY+hXRcupGgdiNqpiSWFTJBE8VQ6CYGSlSnWkxNWXxNJQEy/T4IiWFqhIFBvaCATMiEYEYdFASJiDEGZiFL3XGyZpd4QI/z+8X0+EMeK6EF/Rq4zW87l49KvSXhEmOZMYx4lSN9/5uLFkKkPOQzFeTTVpA/DPwnMC6l3CSl3AiMAx8jNf84g+8A050TCEzuLWXZyh7c2SlMocCJh9B2vhTU08pRf0d4xRU7OZH1iJeKhKVRLt0zTNeGO48GeJHOz4rf4NbKC/mjtT/OhF7n93b+Lb916V+w8aI7aF25G3HhZ/mRtX/MecP38NWDl/KZwz/MobPXccORg/zZys+QyIifGBthaGEUy7mOO6Y/A8RMtbYxtn4/9T1Ppy+WyPQTXvCsEUgCWorNx0tX8gz3CHNMYLjTBGuyWLrKp498mhF7hAtH067b/fv3I6Vk+/btj8t8PN5QcwbCLIASEmo2WU+nN1id0qwOhV4PKQSNXJ7IVbAwsZMlEl2npZQY81dpWiaqiBDqoBQiJZ6hEa7aJJlVxryERVsh1NIEeThWQeq4fT+VelNi+k4Fp79M/1GpNz3muF5FSUzGpUdftxlbXqFhQxgmjPbLOLLLwtDgRtQXJL6BmVtFMVUkAq+sM7OyQNPYzKKqkjWXUOPopOV0wUxvBG3DQyKouC0MAqJoHCdOHadqUxGqlycWOm4M1A5ydmVgGLL6EFNTqSnMGR7y44IzsfnJgtvg/oUuY4tj1LY9wj6xjSvkV+nePU4gW4ixDTx8wXl0Jhwy5SbJaMzc+gluu/yZzDDJS+b/gt/zDhIKhSvHXk3Rz/HiL93LLuU2XrnuNyiujnLpAyuYoc955/4Fry3/OZclIcPxcyjJ57FpaSsbF2IKxme4eNsvEjy/yaG6wt81TH6s0WVrEHBP5xVEaJj9YwxPnM+BzjH2rM1i+bchAS//HKbrPud1JV/L34e9UEAaJtnxWYZPJExnG+x1RxFawubo6RTE3ewqnIez4qE6CqNBk8lVjX7cplKvkwiFermM7HaYspv43jhIQXbEpy8yrNpVst4oCSrFKET2OqA5SEVh2E6v/zG3jyxvOOXUx7FHv3+E5UhHKglykCBrvkZzIIaTGagFRYOQmhkkiKuGwPLK6CJE0wL6wsfVxhilQVsR2PFAii4G1YzIqDX8pEBGeLiOje11UbppbKsEOlI4+MoJFm1xMkF+lJxgmgIpwdZDkr5gyUiI5TB5f4XYVqmhoMgWnmnR0zUQgr5pYrnpA4hp2bRDk045lXcrxwZ6mFavNSAjXAQJS/0Kdsan63ZRo4h2Pa2aqyWP+qNSb6fQMLYHCXLfPcFMbobEP0EziqmF8TdvWNl6poLM6RPkYSnlh6WUJ2dPShlLKf8VGHpih/bUQBTH7FTrBJbNojHMlu5BkmyOutJia/FBtB0vetyOdd32UT6bv4qpTI6su0LGXMc5hwrcu87j7ju2YFsLvDn4Xe7IvoK3bPx5RmoBzzm4j5eXP8cLN3yOczN78Xfn2f+vT+MW4yXcfeF5/NJDn+Jdsz+NVPq8YXSEWjTK+ccuo5bvc3j4brYcz3H+poj63udiVG8iVhWOlndyTf2fAfiXiRfxgmOfZW8rDSimW+GCKydpek1unbuV56x/DqqSRrY9e/ZQLBYZHx9/3Obk8YSS0RFWHiPsEBgFHF9QDwduenaTQjsNdvVCichVcTQLVabd2qvKEGPBKl0rfRgyNJdE0ZECXF0jrJsk2RrjrmTRVtBUh0QJyUfp9rVuju6gQtLOVzDDDnJ1hCgyKJgeVaUJwKSSXtLZ1Tb1jIIaqJi9cSaZo1osEasCaQqoZTDySxSUtHKwZ3wD6+ZP0MqkjXqmUmV0eQ+KMknNWYBBo2Esm/ScUYKmzqZkgWUxhWHWQCZUh/sYXqrSMssEzN/H2vxaMnqGh1cfplKpYBjGGR7y44MzsflJQrL3U9xemGJNLsM/568mRuGFy4eZr+7Bn95MN59ju74LPzCp9cdxe0VCqWEUG8ytmaQ9dTnXrbyHP/ePkVF1Lht/HcWeznNuW+Jh7SO8ds0bEL3LuPLBRaZ2B+RK+1hz5V+y5UU/w/pn/RqbLv8ldj7rpxh/0X8SzcTceUTlHzsGO7yAH2om9MMx9nrX8qAe8rOqhUwifi1fJlrvYHe+jNTOo5HP8eITLioKrdxBTsRdkJLDesLFsouCpLeoYY2ZqMLgkUKfvjBp9UL8EYc19WXiWhp/Ku0mjdIQqlRQAo/tmRW8ukOkamijOghYyMyheqn2+kjURPQD2tm0RyF2XGQMM66Hve6Zp5z7Xu8AUsbs7/XRTI1EU0BKZKCftJs2w7TKawwuhUfNQlK76VRK1DBcevhkFYciXuqmJ9MH9qZUULMRGaWGl+TpS4vI1nHcHnq/QY+ISlhEkX2QTVYMQZZBgqwKkkhQMiQdqZNVfUgE80oHic2Ut0LgaKyQYMmU29zQFAQKnmFghCl1Qph52qFFp5SqdZRigfDTZDkTO1hGkywhq14ZMxfS1zWynS61ZqpNr5V8+t3BhJyCZmHbU4CC2z/Gmvwaur29ABzse9+8YWULdJdOWY3+QcDpEuT7hBDvFEJcIoSYGLwuEUK8EzhjZfod4COf+DLSzHDXaHqhTs+t8kx1E755F8pk7rQOQv8TaKrCCy8/l26+DasqYbHC2UcLjNV0vjy1h9seeD5GaR8/l7yFTO86XrP9rXgyw0W7WgzdWub4w0/jU+Uf5ivPuZpruJt7bnkdv9J4K51cwuvGJ9inZXnGQxsR9sV8YfP7sH2VrHIp48NHqO+/gj5HyfQjnnnjNYjqHiIU/nniJbwpeYD72YkeZFhVNa69aIovHP8CkYx47vpUush1XQ4fPsz27dsRj7r6fI9BqAIlW8Lp1fCNAk4QsXQyQW5R6H7dTc/va2QNA1+mJh4ryhATfhXPMIikQkatg/INZiFNg9BKzUIWLMioOSKtgzGQelvqTKJraRDrZIsAGMs2SaLi2F38OD325KAj2my71AoaihTIzgSTzNJwcnSzWQSpkoWRW2IqTJfuHixuYd3cLJ3cNg7rOvm4w9bFWbrOWurOIi1j/YD3FtHJjuM2bLYm8xxU1tDO9ig3a8w5IXqUBQRH5RTesbtRFZUdQzt4ePVhFEU5Yxjy+OFMbH6SsHzHP5C0pjE3HGKXtp2LuZPW3X3cqY0kisaUdow94TkQ5zkeL2G372XtwkNwyIPhLqGjsTrzdLa2383fxzXGjSxnVX6Y8ZrKMx602G2+mx8ffxqd4LVsrne47OYaY59MyO2KyHVrWGEH4zi4n1f50j74nKJTihP+YLnHkOzyifqbcIXk2Z2jWOX1/Ef/BLW1Dnp4PyJpIZ1XkulHPK8Ge60jbF0u4OZyZM0arSMdtuZXuF+bIO5rTNmbSLQH+NeRi1FXPRIgqVhsDfbT8To4sYEqJQsT45hel7zhUzACurMBzazBwsBgqGbV8N11FLQuOa9BqedRGxoih0srL4jrOooEsfF0DXrpMv99jWXUTBYhwE5cgtCkmR3E3iQtQmQ9D6lYZAYJctPS0R+1mx406pUR2EnqpqcoJfRIoRULRDbBUhqAQjWeJHFSsxA0nZoIqEQllLhGgkUcRwhhgASpG0TNHCVV0kSnoKRFkoZIpeQ29lvEtkYfcOI0Ntf0BEfL45sGSpLG7Vgv0Q5N3FwNhEI2kvh+iJSSbJhF1etkCan7RbRiSN/UyXU7NBIbIwQrF+L2T58gK4qJbU/R6x9mJjeD30+b4g/9lwT5TKMenD5B/hFgN6lD0+cHr98BHgZe84SO7CmCQ/ccoSbGuWtUY0hWsQ/kmVR04mN7ENueD4Pq6eOFV1y8hg8ZF1DRx9HcDl5lhit2jWBE8NXMLTx4z6ugfIwLR9/MTx3S+WDhXbxv5LWMqXXeGPwH/3Tst/mPXb/AW47/LXmlzsObs/xUZYJHFJWz5kepxC/i7pnP07VWOOfQJFdsXmTpvldjrX6KUFOoFrdxvfdREuA/Rq5h3dw+vNoqLXLYvWnE2jyWrvLJw59kY3EjW0op33j//v0kSfI9S694FGphiHyngW/msHyfeTmQ8bGaFLrf6KZXIG8L3EGTx7w6zLhfpW9aNOQoBXUZRRRASFxdQ+kIIrvGuJdQs1QcrYSiriISFUiouhVyWir11s2ngdBsCEBi221kZCJFxIhhYSQhYaiwWkppGm53jClmcXWb+ZFxFE9izbnoTpNtvbRKsd+ZYe3iHFJxmDcsdCm5st7BtdYSKxGHGKNkpMG/7eRJ3ISz+oepU0C4bSq1ReatMgIFXTgcYobg+N0AnDV8Fvsb+wnigMnJSZaXlwmCb+mcPoP/Kc7E5icDXpvPHy9S0Ur8R/58XMXguvrDVEWBxLTImlVOyI2EnsaNL3sm7/69v+Nn/t/fsWXLMDcoXyVz5zHEaAu0hKByMUb77/mcdNmenWK88Ew2zcacd2Q7uzMf5uVrFrmX30RoRXYU6py71GT9F0Pyn1NQZ6FT8fjykIUlJX+/uMqauMeHl38Cn2lass4lI9tZbR7m7UMTuBuKOO3PEhnnUC+OcfXxJqVI5c7ybawugzRM9PEF1s8rrM02edCfQiiSHdGVVMTNfLV8BcOzLooKthVyqVul6s0x3E0rnstjFWivULG7JFKjP9cnKSXsZyMhMZ4S0OivZ0yvYwVdhvt96kNlJvRlKEq0Rxv0Js495fR3unsQis1CEBDlh1CAXNyjH2VOVpC1ge5wxneJtQym10eLItq2heqlyha66Q3c9BSiRMcfNL3l+wbtRKA4EkVLY/VqMoFig+X7SC1DE0klLKFGNRJtDCsIqRkqJmrqptcok1UlVUVjWE2ViOIk7bPY0PNOKlkMDTr5ahpktAKuoSMAp9Mn0nJEUqUUBmCXMf2AdmBhyJhsmEXqTUwSmnEGhiSBqpDt92jrOcxYJ5uJiKSKq5indcHLZDbR6x1Mpd7iOqaAQ71vadQbT6lxLD50yn091XE6mbdASvm3UsobpJQ7B69nSynfKaX0T/XZM0ixrjuHimBvdpgt0X5q0SgeIevknVhnveBxP17e0rni4vNRCw2MuktUrFCIda6+f5ie2ecT+a+x97Y3kOgu/Yv/kG3We9m4cjYL9b/nltbf8Jn2r/Al/eV8efsMd1+m88f+CI9ImOpUuPDEj3OieJyHxr/I+nmH5rZrybVt/IVxehzH9hJe8ms/CQ9/lASFP5v5Ud7c/xL3yrNQEoHil3nWdWs52DjIg9UHeeGGF56sFu/evZtCoXDSUOJ7FWp5aGAWksH2u8yTLvlpdpNMb1AhKA7RcPMUrD6ymwbdE/owubgPumRObqCkLqKKAkhBqKnYHZ/QWmVioIUc2iNk5RLEBrbi0g3yjGsL9A2HVv5Rqbc6UqpoWoidZOjby2S1EqPxKg01y0o5TZAX/QqTScr7OzS9FhEL9FTYgvVqFSlgXqukShbAvJau0O+Ieyctpw9pChODRr2WndI+drQPATBeGybbnaNlDxPkAjQ/Q4sCZuMghB47h3cSJRH76/uZmpoiSRIWFxefuJP0A4AzsfnJQbjnY+weG2Pj2CIPiAuYkLPouxtEhTKR36edjEM/y6uffwWbz38aANncFJf/0rsYueTpvGB0F85NxymsOUGsKWTzO3iw/a8cIuaC0oU41kbO29tkU/WVzDvHeP369/DjExfwV5nLuGPU5Ng5Prue1ufPdqj8YaXANj/gvfNLOK7De2Z/iDrXsqL4vCFTIOpXeUMmi7XVQgv3oIbHiHKvpdCLuLFq0FX6bE58qqZEELOvF3C+1kQKSW9exRrX0LBpWYdYsCfoN3yiUZv19SWs+TyxDBlbWSJSVeqlMnTaTNpNfHcKGQuyIx51ytTNBjlvlL7MMiR99H6HQhzRy2aZMg+mmso9H8/MglM+5fx3OnuJtFEkAjefxqWi7NHGomcJEiEhbJ+0mw4NBzWKyHg+PSdH3E/lLlU7oIfPMIKGzKENTD2KfYPWoNEuMtL3WvEIqp3GYSEE3SRNkJVolVifwAi7LFsKDiZSNwkbqVnIkqoxKdKCgxqlK4frXYm00wQ565dw3C4N28TWcvT0QeJcrxMMuNVDfY3YyaO7ffqxQTaOyIRZfL2LhiREpeqUUJTUWCQRCiLKk7UTQFJPdFg9eMo5zTgb6PePsb6wFoGkovn/lWKRG4dMBRYfPOW+nuo4rczbt4MQ4rcez4E8FZEkCdv0Jo2cTVfJsqYxx7rMNC3nAPkZCWuvfEKO+7rL1vFefSsFMYniezQnNlPoZHj1l2z6xirvHfs0d97y4zQOPxN9+nb6V/4RtRt+Bvf6P8F83rsRl36FlhLylweH2aVEjHdGec7DP08z0+eLW/+FQldH1V7ID+l3sbLrZWi1DxGpgmDjFeyY/ReQMR8cezYjs8fZ2tvHQdZh9ieZzShcsWOUj+z/CIZi8MKNLwSg3W5z5MgRzjnnnO9ZesWj0IYrWJ6HZzmoSUzgDtz07CoisclHAfXSCF7fpKI1yXQltt/nmJVKvWWUPseZpqguI5QcqhwoSgRdQrXL2EC0vW+WycdLCBQmCPHCAuP6MeqZLL4VE6kWtrtMNLAwHVNVjmUO48gyFbnKfGaYXL9OSERNCmYGy45HJ9KEV196VMmiDpqgJSwm3BXMwOeosR6AEXsVKVLL6SW9xYidVpBbRjrGyX5auVH8MZzk0Ua9ALVfBCGoUoaVRzhr+CwgddQ706j3xONMbH78MHfrPzDWqLBnRHLMKnF1cCuL0Qy620eYFkY/x0UzOtsuf8Z/+ezUK/+RkfVTPGPyMOrnWqwfv5++47DJsPmX7j1IoXDh2A0IxeHyex/i3OXfIbKezzF1kX8YmePnxob4ifER3jZUwkPnp1fgJcdn+ML8xXzoxLPp6T+Epya81taRQY+3xC3aEw6t8SLZ5kfwM9fQzVS4YK7BJhe+MnQzyb4sYb5EsTSLdrDH9uIyt6rrifsaa50dJNq9vG/0EpSaTygl0ZjD5vY+uk2JgspQv8vKyDhWDEocsjO3Qr+WJ1ZVcuMSqcBCZhann/aRlEKPpOvSt4oAZLJpzFjX76KNnX3KuZcyodvdx2piY2s2q3YqQVlI+nQUgxwKriPAczGlihGH+GYGEYXYfkAvk8MPQ/woi2J5eCJgWApWkxyOmiaw5Y5Jc+Cm1zPTJLEXD6HbKfVMEeDFMaU4jxXWifQJ1KjGXEYhnzgkuoHfdtAEHNNVSjJE0WMsr0VCxLSnIQcFBcIyhW6Veq6Aodp0B+7O5XoNf6CFnO+ruI6D6qaJthN7ZKMsbbWPIlKO9bHeFHkrxBgoT8RhGUUBLRewGBqwuh9OIaWZyWxEypAhNcZQDLKywaH+tzxTCwHj58DirlOeo6c6vusEGfjxx20UT1F8/HNfAcPhnvG03XbiiMszGSFo7SPY8WzQjNPs4bvD9JDD+u3nUyp3MKtVpJNDLxhIWeGXPyoQssNHt/wj/7La4r5P/DAn7rielf1bqR0sMHv3MJ+6dZw/aWQ5brlsWd3O83f/Ci2zycd2/jVaFLJ98WlsmUloPvgi1NZuOnoPw9f5id/9OeQ9/4Cr6Lxj+kf45frHuDPcknb39ieYumgEL3b55JFPct3a6yhZKT9s165dSCk555xznpD5eDyhjVZO2k0DlGoKaiwx7DqhzFKK+9RLQ9CD8bBGvq+S99vMOwOzENlhWZYpKd9sFmImPm7HohIOOMuWgTJoOplKFGRYIpfM0shkiTUXzyzg9FdwO2niXdElB60TWFGFEk2WnDJrFhdoGTG9KGa8V8SWfeZG0xuXaAhkrGDmqyiGSoxAKSTMLC+wYu9gWVXRrQUq9cOYySi1zAK6kY43FE1cewjZ1ZiRS9TEJLaRNspUy52ThiFzjBPOPsCoM0rFrvDw6sNks1mKxeIZHvITizOx+fFA6PGxuTWMjUXcJJ+HLn02HTmK1C3qQmJF4HQXuPbH3vjff14Iiq/9N3YMNVk7UqW7J8M29V4apQrn6nv4q2iFcZHhnOkXI2Wf8x/8BC946FpU87f53Y+dw+8c/hn+9Ngv8luP/DJX7Xo9nb1XcHh2jJX+uWjZl2EqCi/KmiidBf7APcG9I6O4O4fR3YcQSYt+4UamVzx+bMUkFBF5Zz/Hky6oGovZLuc1JFN2hz3tCoqZsD26ijFxE58cvpbcfB9FASMruZzDrLgnKAUpJWB2zQRar0bF7mFrEZ3jHq2MyZyZykKu2qvE/fVoIqLiLZN3farDFVSZ0MtGRF2VkTBE2/ycU05/v3+EOO5y0A3YVt7GvgGdLSc9OqrFSBTSyQBugJXoGElMz8khYh87COg6Wby4SxQWTrrpjSBYjgsUlEEzXN8+aTftahJd9AnjPKaTFgHUJMRL+gCMuh6xPo6IF1hwFIoye9IsRAhYsAQC0DIxdq9HX+9RiIoYIkAICKI8pldlpTSMohv0jXSFL9VCDpFIFM+gkdMh6KHHEivsoUmVQIlJBlJv8+1JckYPooHUW6+Yft1GXJZ8G7wWdFe+7bw6mY0AeO5R1hXWQTDHrBfgDvpYTmL8XFjZC6H3X3fyA4LT6SC3v82rA0w8SWP8vsVDtx2krkzw4JDDiFxCHC+gCQVn4SHyTwC94hvxY09fzz+qm8kkaxG+R310G5YW0rFHece7XOzGDMcm9/H+C/6Df8ndzYf6Vd4dJfxVJeBLMy1UafKcfT/GVQd/glnna/z7OX+JSDwuP3wB+y6+ng0PTOF3HJL2V1Cl5KKffzPWl9+CiEP+fOb1bNq3mws5yr2cgxEMU8Pgpdeu5zNHP0Mv7PGKLa8AQErJrl27mJ6eZmjoe7/5Xh8bwfZcXDtdupusMXDTaxHIAqUkddMz3ZDRYJWMp1Pw68wP3PQKdGgKh5y68k1mIaGu4lazFMQyepKw4Ah6anqM8VhHxllCr03TzoJI6GaHyfSX6NemkFIwpIcc15dRY5tK7JEoKkPLdRq2gADs/hommWWpNARCIg0FWXcw8gsUFQkIDoxOs27uBI3sTo7oOjY1JpYOEA4sp/vWNGlnSp92dgq3YbElnuOouoZetkWm12HWClETE0UxOConaR6+GyEEO4Z3sHt1N8BJw5Az+O5xJjY/8YgOfZkTxXHGho7yUGaYC7mb1fokVruBaWaRvWGuf9ULMCz72+8kN4r6nD/kmrFD2O0a7WGTdbUDNAozlNRP8CHpsUWMM73uGmQ0T2X+i7zkbo1bz/oRRr78ZXL7ljk3meBl2Qu5pvRyJoqvx8lcx5Cq8iwrIjj4GX6ONreMrkVcUCBQBbn639Mt/zQCnU21Npv6kjuHbkV7uEJYGsEy21SPVjmvuEQTA29eIzeeJRYBHWMfh7ObSaoe0YjFusYSpaUcXtxjaDV9eF+cGCdurjDidIgTC3e+QzwU8xDbiUjoqi71/mYmzVVsv8tQr091pMK41qBfVBD1Qdpxmga9djutXt7dWGVt+VyOyfRzGQJ81WA4DmllQPZjMpjoMqaVKSBkgu2nFAsv7qF4BSyjR1/4FBAsySIVpUoiY7J+6WQF2VcVskqNKMmRcwZmIZFLOJBbG3UjYn2ERKZayDlpgRB4QZq499ICN5qZoHcD6maITEbJBA00U6EbW6hRlaWhCiiCUFUIFYVMrw8CHMugF1jUSyk/uhxbJ6XeVAQ2USr11hvByXh0vD56ENCqDaTehl1W+4Oiyyma6zJOKq3X6x1iQ3ED/d6+1FH1Ww1Dxs8BGcPKI6c8T09lnK6C3AQ2SSnz3/LKAWdIhKfBTGcRjYT9zgSbgoN0chU6Spf1Y7sRG571hB77orUlMmu2kxtWsFZWQdWRk0N0DJP50jB//f5jcPhHCepPp+UIVsoxfcdkTXsr1+3/UV748Fswun2+tOZ3+ey5n8DxJNcfv4qvXvJaXn1rF681hjX3j/RtjaG15/K0i9YiH3gvR6xxPlC8ll9pf4x7gg1EaGQ6a3FnbCZLFv/yyL+wrbyNcypptXhubo7V1dXvi+oxgDE5iuV6JxPksYZBEqZuep4sUorrVHM5bK+HlsRYkUkmWmUpWyFBMBw16KGSURrflCB7uopfzaRayG7Cgq0QaSYSSWkg9bbQy5/kqrXyI+hRH7FcJop08pZLVaTBdGrgSmjXu9RyGkaoonVTqbd6Lk+g6QglwViQmPlFJgYamPeWd7BuYZZeZpqjhk4p6nLWSod2Zj09s8ms3EBeT6sJbadE1Ek4yz3MccZw+6sM1xeYM4eQIsZIMpxgAjHgsO0c3smx9jHaQZupqSna7TbtdvuJP2FPXTQ5E5ufUBz+6t8wSpE7tMvpqBbnN/cQRAVqqkqxHzPj1Nh62elpcsr5r0OOncV100ewvtimfNE+hqsrGMZadkU3cy8RF3E2xsR2hPsQJzKPMNHUeWjnT7ErfxFfaXh8qhlwRy+hFYRs7hzgvL3/xJf2fYSXr7uA6tgI6kUFWtkc2cZ7cPPPJbC3csHBZX550SQQIbbzICe6TWI7gz+0yJbjJttKK3xS7kTGCmdpl2JqX+Qfx69CVAPCRBJNZtjefJj+koVAMFNbpp0rkOgOiueyObuK15sCKchPujQpsWrVKHijNGWOEXrYXpuK79EolZjRD6A5CU4vJFC0ryslfBu02rsQis2sH2BmzsbT0xVXZ0A1cGKVRkYge5DFQSOhmUuz1KzfIzAsmrgYXoGM1iERkkBENEWFEaWJR4QTDuFLgR9Dokmyao0gzlPW24SahuF3kX5ajR3zBYlSJBAnWPoGLWRvoDSk5dKflhkhOqnhUyxHKITLJLbKCgKFNoFh0FUVEIKeaWB6aUw1rCzNwKJVThv8hhIVLWim+0xUHLVPloBVdxg779NRBdlul1rTQI0kRimg3340Qf72GsaalsU0x+n1DrGxuJFON02A93Xdb95wfHBP/gGmWZwuQX4vMPNtfvfBx3ksTykkScJ2vcFSwcYVDtOr8zxdXUfPfJhg67lg5k67j8cCIQRvunoT71Q2kGcLIvCpOpvZMrLCbLlA0zL5i8//K8rSM2ge/SW6cYFINulznD2lj/LpTW/hPy/6IEcmamyZLfPq/o+yd81LecNNXUKvQLz0ATrZGBubV731D0g+8GKklPzstt/kJbf/GzvEUe7gAvSwgBfbPO8Fm7hp9iaOtY/x+p2vP8k1vvvuuzEMg7POOusJnY/HC2o5h45O30mXx4a6NkEoUYwAVziUvBq1rIME4kDBxMJMlggti5ZSZCys0dc1FJGgPOqbKiWuoePWMsTZVSZdmLcFhpYn1lysgTzQQnsCY9Al3S6kesPmkkmSqNhO66TU25SRzq3ixtSKaXIdtSeZZJa+7jA/OoHwSZUsslU2e2lgfMTewNrFORCCZT2DKSXn9QLCwdLpXjXDmJVy41qDB4Sd7VRSaONykUxvjlVnHAoeqpvBFRnM7iyE3kke8iOrj5xsxDxTRX5MOBObn0hIyWePZlk7UuMBbRtZ2aY438Vq1xFOicgtc+WNL/nOeiYUBe05f8qI0WZqbYPWA2OcNfw1TN9jpw3vjI5TRXKDeT1BaZix2S9y06ZlPvz0LLdutzlaDOn3D+Kv3MzKwsf5t2SRV5/9bN573rWcNe5Te9pkymvt34tUCrj553LO4Q5nxxkqocLuic/Tuj9LNDSOqoQcWVji/MwqBjH1RQNjOGEqvpBR8Xk+NXw9mdkeqi7IOCFXGHuo9ufJyCxakjC7ZhK73yGjBqyzm3QXbDzDxKpooEjmssdx3JTGVQn7xK0OnlVAKgqVTNoEPN7vIYc3g3Lq9KPd3oWnjSMR9LVphKpgCB1roN1uRgY1B0RP4EgdDUk7m1bzc/20WLBkSCyviKN0ESKhL3zayhijokFXSKwoXdlrRQLFCMkoq/hJkYLo4To2ltdFbZ0AYCQsABGJXPgmNz1fpOMpmOAlKlk9IPEVjqshCUUm+gsEGZ1FJA5pdXhVA0Wo+KaJHqXUCcwyrcCmU05l6/IRRL6LRJKNsuj6KjkiVoMiRimgZ+rkOh3qiYMZCjL5ADc0iRQ95SGfApnMRnr9Q6wvrkcNF9EF7Ol9C5WiOA1WERYePOW+nso4XYL8/6SUd/93v5BSvvkJGM9TBp/98s0II8t9A/7x+BGX7TKPv3SE3LYbnpQxPHNLhbE1a4iHVeylFki4v/I0pjMN9qwZRpcR77j1Lyn2Q/wjP4W6fBGe4tGxfczAYNPiOq5beCEv672BxtLZXP1ASJxbpL7ycRRRRU8Er3vXP8Ptf4myvJe3z7yWcLbDT2bv5hZ5IQE6mdZ6jg2rPH3LMO/a/S6mc9NcO51aS3c6HR555BHOO+88TNN8UubksULN6ahWgUhLG+VynkE/HPzO6lLqtpFCUC8UiPoKtmqhDMxCqkoq9eYOZH8stUei6CRKahYSNG2igZLFvC3IKgVirYWapJfpcm+cklYjFgrtfFp9NhsSQYJtd5CRhRQxQ2aWQtyhK02qjypZeGNMJWlCemDdepQA9AUFISQbxSoSOG6MsXYh3WZWS28cG9UesZY21p3QfCbsQYJspkF9pp/KYdjuGE68RKJqdMY9VLcIwArDyOVH2DG0A4BHao8wPj6OqqpnGvUeG87E5icQycpejmamyecXuT9X5hJ5J43GNEEYMNwPWJOrM73zf7DqNXMZcsuzubx4AqfaYHlLmYuP3IovFJ7pPMKvyy6g8fzSywlti6tu/yjjywvctNPhPc9bzztfeRZfet5WHrrufPoXT7JxW0j3kgI3X3gWUgiM/iOoUZde6eVsme2g4PLahZCGXkfpHaHq9whyBZLyPJuOGFxYmePz6lailsZMeRt97WGO2SHHjQ1EdR9/KsPmlTnKC0P0ohblWgMBzK2ZQtZnmci2EQJaB5q0Cip79W0ArNgrBL1N6CJkzFui2PdZHa6gkODlPOJAYV3Pxdx03SmnK459ut19zIc6I84IBzzB1oxFRrcxlPShJA6HaGQEIhTYsYeAkytsj7rrrRgS2y2hCImuu/SFT6CmbnotVcGSKRupngj0bEBGTc1CAqkT2gaO18Pp1mgSMhyWUOMmyB4NVeLI9J4VqSqJZzCkSVpSJ6+mBYdlNa0Eb+s1SByNNpKSn8b+uhaR0Qr4xkALOUmItDK92EDVUqtwyw9pByaajMiGWRSzhk1MI84gK+BrKtl+j46WxZA2BScCBHVhn9YFL5V6O8SGwjoEMaOaz55vrSALAVMXwtw9p/lyP3VxugT5DiHEx4QQPymEWPtkDOipgnu/epCGMsquoSwTco5osQQCRru3Y2y65kkZgxCCN12zib9kI2XjXBSvT5KUaW30GDL73Ld+DDtwefv9f8d0sMq8+0Lq9d9hpPk2bjj6B1x97BdYO/ssao0Jsuo8BzZ+jcaeuygHJ0hUlRv/9B3Yqw/CF3+brxXP459K1/LTD7+XfFzlTs7FiMrEcZYrrl/H7Yu380jtEX70rB896Zx33333kSQJF1100ZMyH48HHrWb1qIevpHH8RVqwdfd9IqttKFjtVgmdFUyhkVw0ixkmEl/Bc80caVJVq2BkiUREtfQkC2V0K4x2Ze0DRVDL6Mry5DoGIpHKygyqS7SNbN0cgYSgePWkImKoiTkhYlrrZDRSowmVZbsMsHAXGRRKMwMJOeOTKYVYW0g9ZbLrYIqaGAzGSxj+y6HzFSf2iosUGz3MeIsdWuJ/OA5xlcaBFYO01UpyzZtOYltph3qS8UGepgudc4zRvXg3RTMAmvza9ld3Y2maYyNjZ2pID82PGGxWQihCiEeEEJ86vHc7/cT5m96K5VcntuS5+IrOjvq+xA9n6XCJIk3xNNf/oL/seKOuOZ30UTCpvVtxKc1eGGV8++7j0DJsFO/k9/BIy+zXDN+I4macNG9H+L1nz2GHkb0rRz3r93G13ZeyJfOvZivbj4XTy+w88RB1O4BIn0Ut3AV246dwPJa/PExE0vqrKx7P8d2JTC6HkWNObZ8gvPMBkXV52C9hGrFnB3ewKT4CH8y8XzEkpeufk06XNC7i+YJA0WobFhaoG879HJDyH6XmUwNz58i7sWYowF72YynBMRSYdXdwJRZxeq3Gen2WBkZYUxt0R5SSFa0NOnYfP0p56rbfQQpIx5sNzln+Fx2dVzOy2VwDBttYIbkh2M0B1rI9qC5WSWt5mb66YP8qqlgDdz0zIFZSAGTHAEtTSHRRr5uFpKLsZU6oLASTxE7KnbfRdEtVkWcSr3FNRKljBVEtHUNXSpI3SCuDVFWJTVFZ3ggIRfItHF5a889KfU23EnjYk0XqRaymTY+FlodQi2tSI+7KklmCMPt04lM8nGaIId6AxVJgsIJcwxdEzhJjBQKxENYJggtYSnUTmvwkctuJUl8ykqIoRgUZJ1HvjVBBljzNFjZA27jlPt7quJ0OsgXAr8w+O87hBD3CCHeLoS4Tgjx/VHy+1/CmtYCipActCbZ6B3GL4zSMFYYW1eH0Z1P2jiu2jLC9ukhdpdzOKsZkJKjwQ2cv34fJcvl3g0TuEnE27/yV/zene/BbHS4v+vyPrPFx+0qnyse5d+n9vPJTpsLP303JWWWSNd5+e+/jYq6Qvz+F3PEnuAnN/0yr/v0e3ju5HE+pdxAIhWyjY3sKwhedPEEb7/v7Uxlp3jRhhcBEEUR9957Lxs3bmR4ePhJm4/HCmFrCLuA7TYGdtMxy1F6GWlWi1In5cdVi2X6fZOcrdGWKdd2QR1i3K/SNW2qcoKCtoQqCkjANTQybZfQWmVyoIXsWyMUkwVEojNMgBvkGTeO03CyRIZHoGdx+sv4Xhp0RzWFo5kjOHKIsmwwlx1hvL6Eq4S0koiJbhZTusyOpUug6qqSKlkUltB0hQAVsxgys7TAvHMeq6qCbi4xvrwXVUxQcxYIrElAQtKmlZnGa+psTU5wQp3Cc5bRw4ATRowiNQzV5ricoH30PgC2lbext55am05NTbGwsECSfEvn9Bl8R3iCY/ObgL2PcR/f1/jkgy02FJfYZU8xJKtklgSF1jKTsU9ZVFl77gX/851WNiN2/hDb1SVyQz1Wu1OMbDzEhoOHKGoaHXGYt9JjTFa4eO1LEASU5j/ML/37LJfuXUEdXCtKElPsdRAy4eGp9bSGz0UqMRc9/FX0SPBrC3nKkWBl9BYO3SaJdYte1qGbn2PrYZOnjR/nVrGOcFFjdGoMV61iKvdz6/BzsY91EQWNiaDBRZnjLPdPYIs8VhxyfGYax+1hKyFn5ar0VodIhMLoVAdfmCw4Cwz1J2jLDCO4mG6biudSL5dZq+1HzUjsdkQsBEycf8qpag0a9B5st5gauoRWFHN+3iFjO6ANmur8ykmzEGsgM2mHIRKVbCctBtQtFdNP7y+P2k1XUDAT6ApJolrk+hrNWKBkJbraBGAlWYOwwfI8YiNHW0IlKqFGq8TaGszAZdES2NIg0Q3CRomsIllRVSaVNN6rQZogb+pzUurN9stk+y2ajoOpOnT1gf7x6ir+QA1uuKfiZXOovRYgyEQumShLU+vDQMniSGeakuVhxOn/w8HfyLDLomdCrwr9+red32wuXdHr9/azrrAOERxlJYioBuE3bzg9cPqd/cGsIp9W5k1KeYyU7/bbwE8DXwCuAW4RQnz6CR3d9ylS/nGL+ZKFLyzWrCzwbLkRl4cJdlx7Wu7V4wkhBL/x3G18PM4zVNyK1uuho/N3zrN44cxDjBR77Jmo8NDaMpubB3j3rX/EO/f8Ka9e+U/Ob97KZUdu5+e/8BF+at8HWakIjEyWV/35OxkLHiF+7ws4oVd4xVl/xDVf+iivHrmfI3Kcg8kaMtE0/cTkqhes54snPsuBxgHedMGb0NV0yf+BBx6g2+1y6aWXPmlz8XhACIGaL1No1/HNHLbvszCgQGh2k+Kg72ylNMRqv0Q+EyL7TQBOaBXycY9Yh+NyIyV1EUXkUaQgURSKbgdPdBh306DXsXIUo7RBZEZCEg6R5Ri1bJZY9fCsAk5/Ga89BsCwHnN4IPWWi1u0zQzji0s0DUkYJlj9tUwyx0J5BJAkhgINGzO/SGHwlZwrj7Ju/gT1/A6O6DoZ2WB6ZZauM03dWWJFbMHRQkDSzlQI6jE7vCMcFJN03WXKjUXm9GESNUCLM8yJcYzqwwBsHdrKYm+RptdkfHycMAyp1WpPynl7KuKJiM1CiCngucC7Hqdhfv/Ba/OwtYmC6fFgrsBFyd00qyNUswWcVokLn/20716v/cpfQZExM2M+1h0BzWtVth/bRbHR4gJjidtFh3dTY0M8w3kbXoQmIqLO+3nmg0v86n+0eOltdc452iTbjcl0Pcr1Oyis/AlP2/VZaoUd/OpcnrVBgJs9wQMn7qLT9VDXb0BRQ9xjC5yXX2ZI8bi/OY5ixlyUvIQR5cP88/AFtDsZoiDBX5fn7IU9aAfWECQepZXVVN5teg1J7RjTuRaaImkf7NHIWazmJxFCspiZx+yvA2Ak6EK3R8cZQioKw/njAEz2usTlDaBbp5ymdnsXUi3SThSw02a+8/IOGcch0gR6EuIFQzQz6Xkw45TGlvFdpObg9HsocUzLNjD8tIKs2T5d4TGMIIgNPCVNBks9I60gKxAbaWLdiMdRLFCkRFE0eknC8MAsJDIm0IMWc45KDjuVemtmMBQ4YahUpIeixzj9BrEImfAdhJmOMwlKZHqrrBZKqLpFx0gDb7lRxx+Mx3QNGjkT4bXQYrDCbir1pkYnE+S59hRZq0Pou4gkodtMHQOV0T7V3nemZCGEQae7h02lTXQ6qWPe3u638JAnLwBFgxN3nPJ8PVVxOpk3QwjxDmAW+Gfg70kDZ0NKeTHwx0/4CL8PcdPXbkZYDveNp0Fg7LDPlLBIZo9Q3Hpq7tUTgQvXlnnuOeP8k5En1zobkoSh3ib+sDzNq8YeYHLGpZbJcOuWNdy9fhy3F7P96EEuP3wva1qHOTpqc3SkyLbzLua1b/tTinf+NuLff4wHMpt4yc4/ZMcd/8rrkjsp6x3+PbkeTTGxa9PsHRI85/wh/uqBv+KsobO4fiZdVouiiFtvvZWpqSnWr1//pM/HY4VSLJPpd/GsLFbQZ16oAze9BpavYyQJ1aExuq7DkNai1PYxwoBjZvqU76gus0z8V7OQuEfftaiE6XLWoq2SkC7NTcY6Mirg+x1algMCOtkKjlvFq48RRRpl0+e4voQWZRjyU43M3GqbWkZB9xTM3hRTzLJaKJAIAWqCPi8x8wuMRenS5F3lc1m7MIdrF1gwDIaDPtvqCT1nA7ESskeMMmqmy5dtO+XXn9s+RIDBlnmHTG+WldwUat5D9DP4WGTcRYgjtpbTG92+xj7Gx9Mq9hlHve8OT2Bsfgfwq8C3Le0LId4ohLhXCHFvtVr9Lg/zvQtv14cZzTrcG19NJDQ2NI5hN+t4zhhx0GbHM04tT3ZKDG9CnPVStkRzBNPQ3T+Ce6PLlV+9GSOCZxuP8D4EHxaHWR/N8LR1L8ewM/idf+N44f0Y0U2sn72Vqfl3k/R/Gb37bkrudqzsi/jL5QNsiF3Qu9xa/zjNhZjJqYtooDGnHGbzssJl47N8QWwjXFAZWzNCKDzKytd479iN6Me6qIbAycU80/oy1YUAQ7HZsjRPz3bwciPg9pjK1AnCIbylHvFozF3yAhIkVaNGp7ONjNpntD/PcMdlaXwMjQQ/5xN7ChvcPsbW551yiqSUNJv30KCEpVosxAWyqsLmjEUmmyVUFJy4Rzconawgq2ENIcEJPCLdQYkiMp5H23EQvkMsVRTLpy/SCnJN5tEHld5y16A5aITumanUWScaRsukq4FCgJ/45BKHbNAi1idQ4xWOZxXKSY5EN/E7FqqAI6aCCujZmEy3R0/vY8fD2EkHRQEvzmIEVZbLFRRFxTU0EiDfbhOqEboCgW+yWE6PPZyY6AMlC1WCLWIy+Cx0x3DyPs0oINvtsrJkgJQYwx6ddposs7Ln286xouhks5vodvawtbyVbiet2P8XmoWRgbGzYfau7+Tb/ZTD6UqZbwOywFop5QVSyvOBbcA6IcTfklYvzuBbcMuXDtAUI+wuFVgjj+OulgmJWa/dirLhMQTXx4Bfu2ErK6qgMzWJ1XIQQmDVr+ftpQo3OvdyxeYVxjMhZjbi+HCBvZPDHBgfolPKsG3jFK99/bU8Y2YP2t9fRPLIJ3jH9Kv50U1vZN0Df89PNh7m3NIi7xE3EqKTa25nUYUXv2Qzf/fQ37DSX+HNF7/5ZNVl165dtFotnvGMZ3zPO+f9d9DKw1iuh2c6aHFIN1RRE4llV4mSHEOhy+rQCFFfZTysUeip5Pw2cwOzkKzosUqRolL9JrMQjZBuO4utVnGimAVboWOkD1nDA6m32e4QUk2DZ6s4giJjtIUscayRsTvUSYP+jJomvHrbo5bXMWIFpTPBJHP0jAwrwxWUCKw5Dz1TZeNAamhXZsvJRr0FrYAjE7aGEOlpo94RVTDppMdoWmkOta6XJrnF3hiZeBnfsPEqbbRBo16NIo3ZR9hWTht59tX2MTw8jKZpZxLk7x6Pe2wWQjwPWJFS3neq7aSU/yClvFBKeWGlUvluxv49jS987N+YGq7zcKZCXrbILYLltxlpSc6+eBzTcR7bAa78FZQkYksmZPRwk84GC39LzCW3fhUdwQ36Hv5BFrlFm2M4LvO8yo+ydvQiZo42ENXb2T38cU5U7uOyvM9vTLb4/fEP8X+sDzPS2EosPD6z+K805j22j1zB0bKHr7VZu6fDlWuOYCUhe5dLqHbMRclLKWv/yBcz4xxTdiKaAd7aHDsWjzDl5al6c6ixjRGHHNmwHqvbwFYDzsqt0KtNIxGMTbdZFcOsmjXy/ggL8TAzRhXH7TDVbbM0PsaMvky7rEJVRQDsePEpp8fz5vH9Jfa6MWcNn8XdLZeLChlUIcgW0nhZTLp04yxtB6SQ4HcwEoEZpW56ysBuupvJE8Qe/bCIZrupWYiEapwnq6Q9E+Wu9XU3PV3BVpoESeEbzEIC/DjVRR5zA2J9lESeYMFRyEsbFAXPSyXoVh/VQrZj9LZPzYxI5Ai5sIawVFqJgYhXWRqqIARIIeiZJk4/1UK2nQzNwKI6kj54jsQaqp9WtTOJgaN2KIiAFW8YoxTQNXXyrTZV38YKBNmiTz8wiRQDlnafcp6z2e10unvZUtqCknQpq8l/z0OefhrM3wfRD56D/ekS5OcAb5BSdh59Q0rZBn4KuBH44SdwbN+3mGwvo4iYQ+YUG/uH0cqTNOzj6NvKkP3fuaGsKTv84jWbeXffo2xfhIgSVGFSrV/Hu/IFLuQA55xd5/KfuJGtzxJcd84cP7/lNn5q663cYH6Y4Tt+C+/oHbx7/IX80Hlv40N2n027/pb/u3yCSysn+Lj6fJbkEOPOVpR+loWNNmunVvng3g9y49YbOXfkXACCIODmm29mcnKSjRs3/q/MxWOFNjJw07NTSaF8XUGNJLpdJ6TAcNyhVhpC6ceMBVUcXyfvN75uFiI7tLHIK99sFuIaOu5yjjhbZcJNE+RYK5AoIc4ggM+3J7CU9HJsPir1tmwAAttp4w22m8ooqDIiiFRWywMdZX+UyYGSxb61GxGuRF8UCEWyWUmVLA4ZE6xbTGWNjmtph/dwsU7OtRFSYUWvM2KlQdRTGkSGRT4QmAT4ycTJRr2VXBMtSss7i4wwu+dOSlaJUWeUvfW9qKrK6OjomQT5u8cTEZsvB14ghDgG/CvwLCHE+x+HsX5f4SZ7I1N6g3sKRc6T99FdyjFfnCIOc5x73eOwAjiyFbH9hWyLj/HgulH8+8t4N/YoNxtsOnicsuJxpX6Ev44Ei/TQ0bjMuoob1v4Ez+F5/PT9z+Bn7rycax+4gcqdr2fqa3/A6P5XMxcc47OHPoDsJTx94oUcXTeHH+qo80fYaDc5x1nmPcnTiGoqG6c34Sl1RsRdvHXqlYgjPVRNoI3pPMv9LPWHKggUZk4cQwDH1q4lqh5iY76GrkiaBwNaWYe4XEAoCSdyxyj3pgnQGQ09RKuOFSl0cnk2aLvRnIRMOyBUjbQieQo0m6k4y231KjtGLuNA3+PSYhons4OfedmnLQykcPBskJ6PKTWMOMK1sojIx/F9OpkcXtwnCkqYZmoWMozCYlKgpKa0jKxf/LpZiCbIqVXCuEDWSZvtjLBHFKSremMeJNowEbPM24KcTO8BbpR+Xs0ONOiNCLowb0IkxygGc0SOxiISS3aJNI2WlsZlzzQw/DT5VMwKjcCmXUk7qPNhQt+LkcTkgzy6USUrI2phDmUooW/qFNotmloOM7YpZ0NAUBP2aRPkXHYbYVhnQzY16BpWOv9VyQJg5nKIvB9INYvTJciJlP/V1FtKGQNVKeWdT8ywvn+RJAk71CZHhy1CYTC1vMTzw/W47j6MHae21nyi8YYr1rFjTYGPGAn57lkgBKYywmz9ev60WGRH8wDKTb/NxMU/xNhPv4fPvOj3+btLf5Y/uuiX+I0rfp+3X/MnPJB1OVb/My44uIu3t5a5cGieT6k38GC8kUphnPBIhTutiJ9+yVp+7ZZfYywzxpvOf9PJMdx+++10Oh2uu+6678vqMYA2NoLlebhWWt2dqoEIUzc9LylRTppU8wVs16UYdTEji0y0wlJuhATBUNLEEwJbaYMyWCOUqZKFu5ohclaZ7AvmbDCVApHeRQwWvFf641TUKqGi0y6klSyzEaMoEYbhoSU6koSCVWAkrrOq52ln0w/PKRrT3SYAh6bXIqRAW0zPQT5XBQVWcZiUVbL9Hvut9Eam5ucZrR7HSkaoOwswsAiXSZN2boqgqbMlmWVemSI05xFJwjEjQZEapuowL8cI5tIlvG1D29hXT7lx4+PjLC4unmnU++7wuMdmKeWvSymnpJRrSZPsr0gpX/3Yh/p9hNoRLKvMw/FVuIrBlvZhsvVVFD3PsFlnZO3jRAm7/E2okc9l0mOk06GvZWk9B867/0621HUm1TY79Cp/GR1kJV4gkj4ONptz5/P00Zdwff7VXBy9lA39K3B7Lrcu/wd3rHyKzcULuH79K9i/5RZW2kNEneNMtntcM3Och5mkc0zBrsRs81/EjPZnfMEZ4pB6JWrNx1uf4+ylw5w1VGehfQJbKzPTqrFSqWCpBYhj1mZr+OEI3nydaCTmZnEpEsmivUTQ2YFCwpS7QKHjslxJaVSZYpqIbui0USbOO20PTrN5DygOiyGYubQZ8mSCrKSJaoE+HdVESzJ0sgLZD3GkiZFEtDIFSAIcP6CbyePGXTSviGN08USIISRVWWZUqRPIkEw4RD+BKIFYScgpVYK4wJDRJtB1TK+LcNMH+UrgIFEIxAnmbeVkgvwoc7dkgZuo5FQfGQlmtR6SLNPuIrGjsUhCbtBYV9USTMXGs2zUOAYpiY1h2qFFSfTBLmK6Po3AxkkCcmEOjBo6EKOynC+TKArZMEAKBREPY5kStJg5X4flPZDE33aec4NGPRHMMpGZwAhn2d/36H+r5fS6K0CocPim7+CL/dTC6RLkPUKIH/nWN4UQr+YHvMv52+GuO29FsTM8MOYgZMLIwYiSomHO7yG75cnnH38jNFXhT192NifiiLmxSQyvDFIitEnE4vW8pTiOEwfs/PjPc+8/vZAjs7fRKuboFXweqf4Hn9j7B8y37+ftB13+IjrKpNPlfbyYe+NtDJUrcHgDs2rCeTdM88Ejb2O5t8xbn/FWMnqaBLZaLW677Ta2b9/OzMy38zj43ocxMYrturjOwAq6riFDiWL16MsyhbDGai6DHockocDExkwWCe2BWUiwSt9QEUKiDXQ7EwX6hkZQt4msGhOuZAezYcEAAQAASURBVMFRyClF0FZPSr01/CIT6iIdM4trQ6zoOG6VOEqbH4uahmeuktVKDCc15rIj5NwqCZIaEVNtB0P6nBhPq8NqVQyULBbRVQUPFasQsX5xlmO5S6grCoa2zPjyQWJ9kpozz6q6DVONgIiWswZ/NWC7f5QDyhqa/TkKnSpz+jCx5qHGDvNiHLuWujVtK2/jWPsY/bDP+Pg4vu/TbDaf7FP4VMCZ2PwE4Mjn38bIWJeHzUks6TK82MOkx0jN4Jxnnff4HWjyfFh3JWfJI3x6fD3K/Rmiq3tUp4qsv/3/s/ff4ZZcd5U3/tmVT506+dxzc+qc1a0cbdmWbByRsQkmmWEGDxkGGGZeZt4fTIIJYIIHGMLLAAPGMEQnsJywJdnKakmtzn1zPPeeHCvu3x911DKg5CC1Ld/1PP3cfu6tqrurdveudb57fdf6IIdaGSaVOqWE5A+ix9gI57nUepyBixlds8yC/QSPmZ+kYq9wovA6vnn0R5k8IPj4rj9gbmMWOlsUV8u89vAqZuDx8cosMoKbc3fRtj6MKZb4+fFvJ1xwUTSBNmrw2q27aT2wn0B6iFoLVUbM7dpFVJunZLbZ59Rol8eRQqG0q8mmHKOuN0m4RdaDUcbNLZxOhdFWm43REbJqn2oevKrOiOejHnnHCz6aWv1BqqKIpdlsyCIJRXBVahAA0rkIgBN5tFWLRODQtAV0JUkS6EQ0U2kEkOx38HWTquhjdbM4ahOQdIVLXR1mRFRpiwgzHAEEjUCAHuKoW7hhjhwtukmbRK+FWVskQsZOFmEDJaxSMcDEBAmuAjJQKemSujTIDryQt0W8o3ao00QmNLrARDsurFTUEEfP0bEMFCDVbOHrCSSC6ZbAT2bRux0CqZINXNJ+mq7WQg7+EVzsTZE2fSwZE9qgPxQXnUY6LHdtCHpQufScz9lxYivPVuspDuQP0G8/TiifRYdsZeJmvbkdgvyP8UPADwkh/l4I8UuDP58BfpS4a3oH/wgf+7tTNESRp7I5puUC7VaBjuizO/8QTFx/pYfHgZE0P/u2Q/xFvY6dPw5SRY1COokxkqtv4MH2IT5l2bym3eBfPfYRvv9j/413ffa3+O+XnuTehTX+Zn2D12jbXPAneS//nEvMMDw0jLlyiE4kuLjbRCn+HZ9Y+gQ/fs2PX46UllLy0Y9+FCkld95555V9CF8mtFIO04/oJGLd2VDTwvNA6D6hopDtVfFVlYaTwu8pGGoCNVoDoKIUGXO36CcMfFRsrUWkGISKpKdrKHWBn9hivBfhqgrCKOCwhggNcsKl52cYM+epJR1CvY+np0h2y7i9uKpb0mDRmSNBgWxUZ90pML65Tkf16fkBif4s4yyzWiwBEBnqwMlijcygoF9Pp9m1vEglM8OioZMKG8xu1ag7u+iYDS6Fuykag0S/hAOR5ETzAnVS7NvQSbZX2ExNoDl9RNemg03BXUJGEQfyB4hkxPna+Z1GvS8PL+naLKX8eynl83dTvQLxsQsrHBB17s87HJOP0Vlx2EhN0osEh267/Sv7y275MfR+i7to0Agt+s0U3re2SPY6qIunGKmHFESXhJPik9GTmEnJX5Z/l8erf0/dbVHyRznMcaZSRWq77uVvjv8cvyYfpLx4NWqnQXZjgVtOVNnvrfJbvZuJyoI9u8eRYYFj/D6/k55mKbwDpebh7stwfPUcR3ddYrm8RkovcO3yHK5hUB3dS9jYZF9mCykF1SfbVFM2YS6NUAMW0nOMdsapRUnGZBejVaPU7bE5Mswe5SxhDvStAbN/gQY91y3T6y3wVMfj6uGrebDR45p0EmNQdU5unwTAJkAKBcd3qCYFdCBFAl1G1FOxTjndi3slVowAu5dHFSH6wOqtpY4xIqo0VIEVxcWCWiTQkz6OukWIQTvK4dsGyW4Hw2tRJWDIz6OE20RYJLyQqq5iSY3IMJDVIjlVsqXqDA9kcNHAXeNgu3/ZC7nQzqAFPhXbwtbStI1YajG0Vaavxotwvq3TdmyUThWkxPa6GJFBW/PwBlHbS40pMokWke8iZES7kQVAHemx2R6IoTeeeM5nrWkpbHs3zeYTHCgcoFaPN50ea3b+6cG7XwNrj33d+SG/kA/yqpTyBuA/AguDP/9RSnm9lHInButZMFKrECkBc8Y4u7vzZLKTNBPn8I/fAJpxpYcHwLdfP8U7rp7gVyst8tZhQkXFUFU8O8Mj+qt5bP4O7l7ez5lGkU7HJt80MRs2y/UCn9zex3t7387fpN9FT9js2bUPe/Mo3bbko7mAW289x/9+6vf45n3fzHcfeqbA9eSTT3Lu3Dle+9rXksvlruDdf/lQMyaKlcHXJaGik+matLz4BaAlGmQa8QKzlc0T9FQsM0E/ij0pNwZhIW3TpiaLpLV1hJIahIXopBudywQZwLWK5MMVBAoTEiKvgCOW2HYcItWjl8hidzfpNYaJIkHB8LmQWMTyi9j9NoGiUdisUE0IhAtmZ4JxVtjK5gEJeoS+JjEzawwPduPuz1/N7Ooyvm6wrlsM+332dEw8cwaA01qCiUGjXiMu7LC3HS8Ho41hnHCdlpMlzNXQ+nFHdQeH9aULzzTqVc9SKpVQFGWHIH8J2FmbXwJEIU/oh1gMb6Sm2RzqniVRqdMzh9g7KUlmv8Lr1u7XwfARjslF7h2ZJvWUhtjdY+W6AodOfY4RMUbU7uNKDT+d59PKMteUjvBE/iyfWv5rPnT+9/ijpT/g9zf+nA/NnaH6xHFG6kfRGhUUUeO2Y9tc3zvLL/XuQC6GDM1q7PG+lUnj33JR1/md4XcRXeqhOBpOPuStm39F+/6r8KI+nV6A7fe5uGcPiVYNUwnYny7T7e0lqHcQ4x538xokklV7Da8dR8lP99dJtjpUssOEqsZk+hxCgZFOG88Zhsz48z6Sej3WuT7YqHFV6RZOtXvcmH2mT8NcfQCViMRAc5by01STINoCizgopDcgnE6vDsRx08lurLM1zS5t0ccQOUrUqamCSB9BDxTqoUCkQ2wltp7ciKYJbRW720XoaSrAkJ9DDcqE+iSW22fdUkhiEukmfqWAo0jWNY0pJW6s0734Wru7GljK4HtDpNtlttM5dC1Bw4jfHflqDVcdNAb2TMoZDYI+aWlhevF6KwBFkSRxWW2Nk0r3qYYeTqvN5oaGEkmsQp92I40UKmyeet7nnUlfRaN5kgO5AyhRnaIGJ1vPokPe9RqQEcx/9nmv90rDizLklVJ+Skr5vsGfT77Ug/paRRRFHNHqzJcsAqEzsb7JW4NpetULZA+98UoP7zKEEPyXtx/hht15/mfLIqmN4gUhpjVK0+jQHd3N46N38tfR6/mj6uv4QPMNfFD7Fu6b+QHOHvweWgM3hlfd9Dq805PUKx5/kexx3WtO8ntnfo07p+/kZ274mcsa43q9zkc/+lEmJye58cYbr+Stf0WgZUyElUGNunhGhqSrUvWfDgupk20MNGa5Aq1OgpRt0iQmyMvqEJP9DVqGxUq0m7y2iioygCBUFYa6NTq0GBnkV1esBMkgTuebDDVkkKXt9ugYsbyjmSpieg387SJ+YJCxeizrG+h+mqIbL3RmvUslqWH3FYyBk0XLdKilMigRWMsuenKLXQOT+EeSR5hdWwZgTcuTiiJGLQXLzw6+12Z0EDndUetEuk4xjBBESH8UW49fCuVUA82PX27rlFg/+yAjyREyZoaz1bNomkapVNohyF8Gdtbmrxz8hXsYyUc8pc2gyJDRzQYJ0Wa4YnH0tS+BX7sQcMuPYTbKfIdY4VPswd3KIN6xRTWTwTr5F9yhHKMdCB7zx+iaKT6Z6GHp+0jsnqVzaBfd8f1oznF05wShnqasqSj7FX44dTeH2pf4r503wIJLeizkGuX7Edb/j4TY5qeLh6lvXofwI3pHctx84VFmZyssrq6T1otcPX8JKQQr0wfobp/lcGaDrO7RXMwQqBozuytURZEtc5tkb5gVf4xRc5t8c52JepOVyQkSSkAnHdu7HWi3MV7AvQKgWvscUpisegp66gQSuCk76NNolxHVC9iKwBwwF9tPUbFBeAIritckqcSE0+nGJLVsCRL9QUOz2aEjXIqoJGVIS4FQs0l3dRqhQHUijIHOeTscR9gCw/eRuk07ihjy86hBmUCfQPcbrNoKWZlEGiZuLYWpwIKh4sgALRFgdxsEwiUXDJFQ4nXcD7KY/TJrQ8Oomo6rqQSKElu9aQGWCh3PZHVo4JwRGShuPCZTChzRJydc1ntDmDmXpqGRaTTY8iwsXyWTcQGVjp56wUa9dOZE3KiXjCvOo2rz2SvIE9eCkfq60yG/fIkVXwd4/OTnY/3xcBJFhhTOBySEQqHyyMsWL/1iYekqv/Pd17J/LMPvdcbQtCR+t8Zk/1WcTl2ikevjF0bpju+iUZpi23BYqzfxfZ/bbn0Vrzr0ds59MKDeCfjjVIXijX/O363+Ee/Y+w7+x6v+B5oSf4r3fZ8/+7M/I4oi7rrrLpSXMSTlpYLiGChWGsut45oZbDdi83JYSINsM16gt7M5tnpZ0smQoFdDRBEXjWHsqI+mBywyQ0FZRSgZtPALvZATFMNYu7aWUGgNwlWGBzrjhU4RRYnbQurZOCTEWLGQkUoi0aQu4wVu1h6UhHsR21kNTSps+SNMRDH5PbtrD6Ir0TeInSzULSRwxpxg12Zs7H9JnwFAL60xXGlhhg41c52EFc+vjKq0U6OEDY0ZuUFZmSAy4usvmiGK1DFUi3VZorf8GEIIDuQPXE7Ue7pR71n6zXawg5cVn/3L/8KeZJ3HCgZ7OYe7YLHljONKj91Xv0TyuMNvh8wkJ2SZjWKWxEUdzfFo3KExs7HKff3HeVNLkBQu/9e9ioWuSavfoEkKGeVIqQpDWotDymneaXyQ94a/ys9s/D4P92Z4X+UW9KUu+amIG5M/TM/4RQ7yFL+QmeIiPwhll2B3igOdVd7hvp+tew8TyoCG51PsNVmamiLjayhIdqe38cMU9VPrbBcNzicOoig+i6kFJtvTVCKHSdnEbFUYbXVYHx9jv3KB9rACmyoawInn7/eUUlKt3sMWRdJmjotehoSicG1mQJAX7gHA1m2MgRTB9O3LcdOmjGVs5qDJLNWOq67bCRW7H0vKDKtPaxAWoobQUuI1MvZCFggNQj0+rxaMoNqD9EIh6Mgg1iD7ZUJjAiXYYiGlkItSSE2n30ygCrhkKghATYZYrS4No4sRDWOHVYQuaIYJlLDMWnEYBQlC0DYN7G4HKcBKZKh5NlvD8UZQLlDw3D4RIanAxtaqpGVAJUghi9A2DTL1BjU1jSkz5JJxgWbdU1+QIGfSxwHQ/RVyZo5EsMR8z6PmB//wQFWHmVvh0qfg62it/tpnK19F+Ku/OklL5Hkqk2dWztHyS1TVBmOzm5D/6gvESFk6f/x9N3Bi1xB/3p0h0iI62hy3Xfwu7M2DnLHW0I7YvPpNt/Ot3/wuvv3t/5wbZt7C0scNTv7tGosJjz+Y+Bjh4f/BUvcJ/v0N/56fvelnUZVYaxVFER/+8IdZW1vj7W9/O4VC4Qrf8VcGQhUoqTyZZoWelcV2+ywNAj30RBWno6FGknJ+hGbXYZQaxTY4bodLdqx3S4s2m+TJq+sIJXM5LEQhpF13UM1Ncm7Ami1oGQ6SiOSARK81x0kOtvDquTglyizrCBGRSLTwwngBG06apMI2dSVJfSAwntc0JgdOFhemZhGhQFuLf5ZNlRECNkWSgtmiVKtwJhETA81eYaR8Po6cTq5S1fajKSHIPnV7GnezxyFvgYvqBNXuPMlOnWU9T6j20MIky2LsHzTqXahdwI98RkdH6Xa7NJvNl3TOdrCDF8LH3CkSYYGLVp5D3hm0zTZ1a4KDsya69fzJb18yVB1u/EGs8gLflTjHb2vH8dYzaLeXWZ4s8pa//yh/Nz3Cbc1VDmub/L1yjM/r45jnTpK+8Ai7Ksscb1Y43Fqh1VD5o9aN/GL1tTw+n0Or+uw+5LDH/nF66s9yLQ/xy+lxPmy/leZiAnIG9ojgzic/gZEdZa2yQtYoce3cHEJKLu09SqVykgPpLabsFs3yQQgjsnu63CdvJSSibNTptmM3hJnuGulGh2q2hK/pzKROoRqSXK2HbzgwfOR5H0W3O0+/v8qDjTa3jd/GZ2otbsk5mE8XVebvATNNws6jqPH3FM+8HBbyNEFOun2kYqK7HpbrUk+YqL6DJw20RH+QpqfQlA6KEhcTCs1nvJBbhkQXXVrhEHoy3lUTIsKNephSp+B2CPURpFxmxX7GyaLTiyWUlYG1vWFFqM2AjUREKEfJeitEtsbqwOqtb1m0B30frmmiezEpVcxham6CMFMHVcfuB9Q8C1PGjXqqtYmBRKKwkhkmUhXSXj/ekQhH0Q1B6Hgsdw1ob0K7/JzPPJnch6IkaDYf52DhIL12rFl+vNX9pwfveR3UF6E697zz+ErCDkH+CmK0XsVXAxb0CXa3F5h0dtM1ThGeuLL2bs+HtKXz+//seu666RAfc3fjKh3aU2eZUme5de5byH3iWk7/XsSn3rfKx3/zAo98bJEldZm/2vMBPnLkp4lGPsLNYzfw52/7c771wLdellVIKbn77rt5/PHHec1rXsPBgwev8J1+ZaHmiqSbDXqJNIl+h2WhIiKJldxASod80GdraISgrTLhbZJrq+T6VRacmCBnqdMgQVbdQCiZy9ftGRrdcoowtcl4T7KWUFC0AoHeRUQx8S13RigpW7iqRTOdQAKJuo+q+ihKRELEZD1jZxgJt1hKlRAMthsJGG9a6NJjYTwO/1DLAhkJzMwahqLQkwp6OmLX2hLns9dRVRRssc1IeYW2PUktscFydIi8ES+ijUQWGUhONM+zTImZcojTXqHsTKAk+4ieTZMUQ/0FpJQcyB/Aj3zm6nM7jXo7+OqA30MYwzwhbwBgsrpBJmpQqpscetV1L+3vvvq7wcpyPHIZyqq0FwooSkTn7Qq+qvKNH/0jTu27iev7l7hGW+ZMdIC/OXoX5qzHZmObB9ea/N1SnvuXRmksg1brU9oVcc2xb6CmvoEpvptrxAV+KTPC7yWPU1+6BRIa0dE0rz91HzfPfIb5e1OYqk29XaPYbbI4PU02tBFRwJHsOqHUqDzWoJayGRr18FXBorPIcGecuajAmLFNobnGZL3J8vQkphLi5nqErsLRVgN9750xgXseVKuxvvXRtsuBkdcw3/O4Pf9MkBLzn4Xpm0naSSJNRZEhvmfSGMRNG2FMBB23R6DZiCAk2evRsBMgoR3k0BI9uqJPSQq2wzS2EkvfhlrPEOSmbpJSt/GjDLYdr3Fa6OIFsYRjpCcJ1Xzshfx0WAjQH+wiGilBJCGp+0QdwYIpCWSJUXeeKKmxRERuYPW2rQboikkvkUAPfJQwJNTzdEKDXf2QKFnA6Lbphzr5sE/aS+PpVaKBk8X59gwZy8UaVHXdblwpZ6LN6tOR08/TqKcoGun0UZrNkxzIH6BcvReAx5rPQpB3vzb+evHrR8m1Q5C/QpBSclhtcGHEJBIqY6tl3hCU8NbmyR98w5Ue3vPC0BR+7m2H+cXvvZML9hG6/RpPGY+wdLWOd12CzYNrnNrzAB/f9yf8/on/wJ/tfh/u8DbfceDd/M03/g3ve937mM3MXr5eGIZ85CMf4f777+eGG27gVa961RW8u5cGWqmE3e3Ss2I5jWypaKHESG7iR2mGwibb+SGMjs9EfxOnb5Dxyiyl4yaVUlilJxRspQ7qYCGTkq6p06s4eMlNxnqwnICkkkFqNWSkoQuXmptjXFujZSbxDR9fs7F7WwR+vFBnNIWesU1Sz1EIKyylhinU1vEJafsBTn+WMVZYHYq15NJQoWpfdrKQQC+VYdfyEvV0gQXToOi12F0PaSf3Eikhp5Qi44lBo54dE/KDrThgZLZaIuVvUM0MIdI11F78AUCisrSy/A8a9YaHhxFC7BDkHVxRbH3+tygNdXkqY5OVVewlj3qmiB/57DrxEhNk04Hr/gX20mm+pfAkv2wfJlxJ4+xbY/PqDLvWlpl44pOsTlzLVdEiN2pzrHaG+SXtRxk6oTL76oDCzUlyNw+Rvv0I4au/nU72djLNX+fdwY9jaR4/PDTK7+pX0178DqSuEFyd447zD/O2zb9k48yNtP06upLgmtVNhJSsTh9ls36Sg+kyY3aLduMYYbOFmPb4C96KEJL51DzDrYPUI4eZqIbZqDDc6rEyOclB5TyNYQW5psXk7fp/+YKPoVK9F1fJ0oh0uka8RrzmaYLcWIXqJZh9FU7KwdMEybBDy0tclljg1dEiQcJz8Y0kSuAP0vRSeFEf182hm126wqMEbEbpy2EhKTcb27wBfV2QUssEYZpcokmoKBhem8iN0+2G/RwQEMrVf+SFHJPUkiFpRwZprQ9SsGTUAI3D7SqRrVFBMtWK5XIVNcLRcvRMEwGkmk08Pe4vmWordFMp1FZ1MMYOZmTSVD16QqIRslCfJmO38QIXzfepbMU7HeZwl2p90FS68fyNeun0VbRaZziY30MUtpg0xbMT5MJuyM3CpR2CvIMvEmfOPIiScHii5KBKn/wFCQJmvM+jzH5tEMRb9hT545/6Jo69+k2kRR9l7bP82aV5/nA9x8cqx2jznXzTxG/x4W/8OPd811/yb2/8CXZl/6F0pNVq8f73v5+HH36YW2+9lTe84Q1fs4Egzwd9dBS726U7iJ2d2BQoXoRm13DJMRRW2cjlcLodsn4LK7CxwzW6tkNTSTMabOOp0cALeSBJUaBr6LhVC98uM96LKFsqKSVLQqwjQoOs2qfrZxgzFqg4KUKth2eksbtleu1BIpIeMZe8hC0LOF6Trp5gqLxNzQyR/QirM8kEy2zmC8ROFhJ9TWKk1xkZVFHuz51gdm2JSFFY1VNMei4j0kEP42aXRdW/HDnd0ppIVWU0jLcjDW+UpLaNVBQqmRp68Eyj3uqZB5hOT5PQEpypnsEwDIrF4g5B3sEVxcc/81EO0OXRTJpj8iTesqBsTXFgUnvp5BVfiBu+H6GZXOWa3OwE3LtwNUjo3ClYHklz12c/zmZYY7N4gAOizBuVJwkR/Ez5B/iD+lt4bfVRvrf2l3zf5m/ykys/zL/s/DzTVpnfzmR468gePl/5Tnor30mY1AiuLfANlx7mzsc/Tq84zerGBkVzguT6MkPNCpd278aKJEKGnMitoiDYftSnY1ns3rdNRYxQ1xvgZ1h2p9CFz97mJYZrLVZHJwhUjT2px1F1SbHRwTeSMHnD895+FLnUavdzrq9y9fDV3N/0mLQMdiVisvi0/piZ23DSKSIB6aBDK7BpDpK/Zb+PFWmYoU/PSqEEHgnXpzUIC6GfxdZbuMInBaxHOUaUCp70SHpDtKK48uspkFK2cMMMJVGnl0iQ6LVRmnFfxrBfGHghV2jrgkBRUaXAVUG4CUqapIpOUYmtMDtRXNk+1u4j7bh3o9RKI6KIasIioaVoXbZ628IVcXXZ6ZhsZQzo17GliekOnCxERCQgK3qstMdIpvtUIp9svc7GtorhQyrvEgQGwYto1MukTyClx6wZk/ZRtcljre6z94XseV1cyf86iZ3eIchfIfzJBx6mpWQ5nS6yO7pEXRlm29jEOJaJKwRfI1AUwTe/9jp++Ae/n/FihjcY5/mFq3s8+FM38YmfeDU/86aDzBaT/+S8MAx56KGH+M3f/E0WFxd5y1vewh133PGKaMp7NhiT4zFBduKX51RZA0+i2k26UYGcW6acSiKICPsKJja6XAVFsKEMM9Vfp5Ow6GHi6HUixSJQJB1Tx6jLmCB3JaEiCM0ShXAFReqMSknkFUhqi2w7DlIJ6CZyJLqb9Oqj+IFGzvQ4b89jeUOkB53ciVqXsqOQ7KnoAyeLhpWmbdmIUGKuehhOmd0DHdznnePsWo2b7ea0UQzAKTUo1iVKpFHTy+StuFFQhtt000WUtkZR1qkxjjDiSOsl00eJDAzVYJ0SvcXHUBWVfbl9nKn8w0a9HezgSuHvleMsyOvoKBa7WwsUuhUy3SyHX/0SV4+fhjMEJ74T59JJ7hp9hL8qZhCLDoXSEtu3jlG3Tf7d//6fPF5Mc6k4zbDW4zvdz5HOe5xszfIq95c5ob2X7zLfyXvsW3hr5lZe5byD32j+GJVL/5569wTBVBLteJa7ztzL1WceJrW/x6UnXLLGKJXeKrtaHfqWRXf4ajZbZ7k+v0Qp0aXZvBqvXKEzDXerd6KofS5mLnCoOc1ilGeXUSbd3GR3rcbSnmlymku96BP2FY61GuhH3vmC6Xm1+kNEUY8HGi1uGb+de2ttXpNPPVNcmf8sJHIwfAQnF1eVs7JNQzWJRByaRM/DJk7TayXTELrYvkc3kaQdtrF6GRy1FeuJFY+KGGJYVOmIiEQ4hkTQCAWRGpFStwhkEiE1+kmLRK9Nsr5Im4iSn0cNtpBRgBaEbOsKttSJDBNZLZHXYi/ksUGfiOrHBHlPL4EycHrV3RLpzjZb2Ty6blG7bPVWxVV9QBL0DeaLcdFhLDIR/fh6ZqSSVlxyuGz2ixh5j5ZpkK3XKUcOiTBJ0Ynt4rZD40U4WcRZBVawiqM7WP4iW17Amuv/04N3vw78Lix9fYQovzLZyxXAcLWOp/ksaePsai5ylbmPfvQk1vG3XemhfUkYGhriPe95D7fddhsXz53h1//n+/jABz7Ao48+yvr6Os1mk2q1yoULF/j4xz/Or/zKr/CRj3yEQqHAe97zHq699torfQsvKYypMRK9Hu2n0/RqJq4nEYZHoCjkOtuEisJWNo/fUbGsFG4U25+tDghy00pSlcNktVUUJYsUkq6hkWs08cwtpjoxWW1Zeewg3mabCjVkkKHmRriDFL5GtoQWeYRrOcJAJ5Vos6yto3tZJs06ALIbUc7omKFC1RthLIoJ7PmZ3YiuxFiTsZOFtg0SnjLGmakvo4YhZ404ctrIrTBaXiIhh6naq7SNaRQRgexQT87gbnQ5ECwyp05Q61/EcLss69m4US9yWGYUqxJv9x3IH+Bc7RyRjBgdHaXVatFqtV6eydvBDr4AsrXBaE5yxphElQEjGzUCxyD0fXZd/TIRZICbfwQhI472h3ir5fIr62+EQEG/qkLvhEMoJL/0y/+JkxPTPDY2i2ZqfOvWfXy3toYzpFIJx7mn8U3cXf0hntz8QVrlt9P0D+JOpHBvHmK26PNtj36cffNnmSwuceGkhaMX6AUNdjVCss0GS1N7qLrz6IbkcGYDUNl+JKRvmhw8uMk5eZS+4rKt9ml29+FKg129TZxaHSXU2SgMc5SH6ZVArqjoErj+PS9461tbdxMJnfOuSjJzE+0w4o7CIOxCylj3OvsqUBScwfczUYeGYmJEKVpOvMYlSaBHAa2kg5AByX4HhMKa5uJ0cwghMYwuHdGnro0zImo0FIHGKEokqIcCxQlIqrGcohYOE9oayU4HXapsSUnJL6CGW4T6NAm3z6YpcEggdQO/msNRJGu6xgRthBZhdyuEwicXDJMcNAV6fgbT3Yyt3lSVUBV0dY1Mo4mnh9iaTt1LsDIWFw6KgUrf9QmFTypMkFRrOEj60qAxlKZt6WTrDTzFQJfD2AlJqAcs91SoXADvWSQTA1jmCKY5Qqv5BPvz++m1TgJw8tka9WZvA0X/upFZ7BDkrxCOqE3OjZpIoTC+ss3NYQ65PE/2wJWNl/5yYBgGr3vd6/iRH/kRbrrpJlZXV/ngBz/Ib/3Wb/He976XX/u1X+OP//iP+dznPsfIyAjf/u3fzvd+7/dSKpWu9NBfcmhFB013cA0IFINs16LmxtUO3a5SqMYL4UZhiF5Hx0naNIi9LBfVYSb6m7SsBEvRbvLaCoqSQ5EChGCoX6XX1xgbeF8u2xotNd6CGw10QGGhPYQmYp/jai62ejNXLEAMrN7ixW0iY5EJWjSxKOdjKce8qjHZia99bnYXQgq09XjsTnodRcCmSJDK9Jksr/F4+lZcAZa2yUh5AU8fo2KvsiKvImvEY6gnhojckGtb57goxslVO6Rbq2wmJyDRQ/RsamQZ6s0RRpKD+YN0/A4rrZXLjXobGxsv2XztYAfPhUf+/N+y22nxWN5kH2fx5jVW7Vn2jSoYVuLlG0huBg6/nfT5h3nz1IMsj9dx53PkC6tc2D+Lf5XAdvv81s//G+q6yQNT+/HtJLp3np+Y+zy/rBl844TNrr0p0sfy6DcM0X/tKPo+h2+Yf5DXPXUvYwsXKChlLlywcPQiYeSS6nvsXV5gc6hEmJ+l51d5y/ApcqZLo3IdfnmT1ix8XH0dqtbhQuY8hxt7OS+LDOl1pqvn2b1dY373LAgoFS+iqDBdaxAmh2D48PPetpQRW1sfZylIsTt3kEe7FklV4VW5L2gya2/A3riXx3k6KS/q0VUt7CBN3RaIjsSRCXQk9VTc9/B0mt6qGZHqDhx/zA4dXAKlxCgVqpqCa+VJugMv5NQzYSHlaIrIVrH6fSLDoUZEyRtCCcoExgyG12Q5qVKIUkS6iVuNvZDnDAUV0FMByWaLlt7FDEskowpognpkoQRbrBWH0QZR0V3TwOr1iVRBwipQ8xL0c9ugaNj9gKprYckuGS+DapXjDx/AvD4CqiAVxFXjwBtDCEEw3mWlnYwDPsrPnz6fSZ+g0TzJwfxB1iv3oYvn0CGbKZi68eumUW+HIH8FcPH842gJmydKKXTpkrwIrgjYlXwIho9e6eF92chms7z+9a/nJ37iJ/jBH/xBvuVbvoU3v/nN3HXXXbz73e/m3/ybf8N3fMd3sG/fvlek3vjZoKZNRCKPGrVxrRxOT6HsDwhyskK+HvtrbhSG2GpnyTrQ8eIq8EV9GEMG6LrPAjMMqasIJX3ZC9kOu7TbDra6QcoPWUwqdIy4auIMrI2XGxNklS0iFBrZ+GeJLQVVCTGMPnLQUZ11coyEZVbtIbxETGY3CZhsmGjSY25iGgDtspPFOklVoS9BpHX2Ls2zmZtmUdfJh3WmKg3qqV30jDZn5AxjVlz1bSRi/dqR5jw+Goc2s6T8dbZzo2hOFbWXRiKwCFhY3+RA4QAAZ6pnGBmJCf6OzGIHVwJ/u+phRSUuWTkOemdIbjeJGObQzcdf/sHc+uMIr8OR/m7e7rT5mdptqF2FsUOnmLcP4l4F6W6f//q+/8bBhYd4aOYgQSLJctbn9MIfsNp5lKWSpDyaILTh+vmn+LYHPsbM+hKj558g8vpsln1KyYN4YZdIhBydX8Q1TXqlIyz0TjNbbDJsdegHObY+V6NlJzhwcIvz8ji+CFjTO2jd3VTCDPuDTZLVLYbrXeb272Gvtsb6iIa3ZXCg10W9/j0v6F7RbD6O55W5p97mzuk38LfbDV6bT2MNrNw4f3f8de+dACSTscQvRSwBSHkZakkBHYEpY5lgJxFrGVKDaOQNU+L0ng4L6dIRLmkSZOleDgvJdGIvZDUVoon4vEo4jkiAIiVCM2nLgJKfjcNCzElUf5OFlEpGJkFR6LRjL+QL9iA1LxFhND02EyGhHCXjLxPZGitILNmh6aToRzFB7iVsTM+NK+bGMDUvwaHQJ0zmMTptfKky5HdJe2kCrYIvYoY815wla/bQBSAljWr8PjDGOmw2n27Ue24nC4hlFv3+Coeyk7hhm92J5yDIELtZbJ6C1iu/oLFDkL8C+P0/+ixNNcvZVIk94SXaiTGqiQXCG655Qe3V1xKEEJRKJQ4dOsR1113H8ePHmZ2dxXo5mli+yqBmDJREDrtbpW/mSbohKzKu8up2hVxDQ0jJWmmcWifDqKhRbIY4/TZzybhi6ihtNsmSV9YQShZB/CLxdIVmOUvgbDLTCVlIKmgDT2F1YPW23p5gSlmlZaZoO4JIaNidNuGAGKdUDU/pkTaGKIZVllIl8vUyrvDp+D7p3i7GWGN5eASQRJqCqFiY6TUKg3EsZWfYt7RAx7JZNWwm3B4TYQYhYnu4c6rKhB3r4lpaB6kIJvx4UXX6YzhqhUDTaaRrlxP1NsUQy2ceYm92L5rQOFM5g2VZ5PP5HYK8g5cfUlI3pzklYynFVHUdW+1i9VR2X/MyyiuexshR2HMnmTMPcOfwWdRJn8fPHcO2m7Sug0jL4F8lSfddvu1Dn+Sd9/4mI0kIjATB2AwnVi7w/e9/Lz/6B7/A9/3Zr3HjfR8jc/40zvxZ2pFPQlqUiq+m0p+nn3G4+uIiuu/TyExwVl8lTNvckTlDUvOpzl9N1G0iD3r8qfhmhNHiXPYsh5u7OCuzJNQe+6tPMVtpsDIxQU+zuMq6DyUdkSx7REKB67/vBW95a+tuJAqneypjxdey5QW8aegZ60su3A1jJ8CJdybtQWO0TVwtSHtpKjYoLYGuxY1x4SBIxBnslG1ZCsneM2EhT3shW1FEa5C8V2wNCLIOnuqh4FMNRtCST4dmCHpRH0dapN0moT4G0RKLzjNOFl03fgfUBm1Hlhkgm5I5WyOQo4z055G2xpKQFP2Y4FdFiCp0+okkahSR6PYIjDRepLG/E9JNpVDacXEl43ZQUempIXWh4og+S81J0k6PtgxItVpsbgnUUOIU+nT6NlI1X1SjHsCUEd/rqNLk8VaX8Fkb9QahZ5c+9bzXfCXglcPeriBGKi16pseKNs5sY5FXawfod06TP/bWKz20HbxEELqKki6Sa2zTt9LY/R4LKCAlZnITghQF32WjNI7X0Zjsb5Bta+R72yymYqu3nGzQFCYZdRPlaS/kgdVbZz1DkF5nuiOYT0JKzSONMlGok1A71N0CM+Yi206aUO/hGQ52b5P+YBtxWBfMpc/iyBIpr05PtxhZ26BqRsi+xOxOMs4yG4W4qoIu0dcjjPQ6U4NK+KczN7FvKTaFX9CGyEUR6RwUGjpIwba2yZAVS0nCaIt+Kk+ip5KgT4dxFDM27l9MuCiRia5orFOiu/AIhmqwJ7eH05XTwE6j3g6uDDqL9zCS73E6Y5KTFRILLpX0BAWzi53JXplB3frjiG6Fg+5Rvj2/wm8YGawtwfT049yz+0aG9T7adR6WF3LigQrO/Z/mpv0fYcqU+PkRentPkMhNk5U2BU8wJtLsTV/NronXEzlJluV53NEpbn7kCdLNJh3L4dSYRdey+J78PaR0j1r7WhqPnGWzmGRsV5+KMkZf6bOu+iS6Uyz6oxyUm6SrG8xs15k7upeC1qU+6hK6ClfXK4jdr40b654HUkrKW3ezGjrsyh/h4a6JLgSve1p/3KnAykOX5RUAmqZhKgaWGpM3K0hRT4LSFxh63BBnDKqyiW4HNQioWBpmmKQjbbREn5boUUTQjyyCQSrpUMO4bPVW0y0ctUIvymPZsWODECFuEBPwEddCKjYBi6x9gRdyL4rPT9rgRwopzYVQcEnvAzqHultIW2NbRky1YjJd0SIcLUt3UGjKNOp4g+pwtmOwldGhVyWFjd4f9GkIiUSSFz1Wu8PY2T7bMiRbr7PZ1bB9g0LaAwRN7BckyKnUYYRQsYNNTNXE9BdohxEXu8/iVjFyFJKlrwuZxQ5B/grgiNrk7Gi8pTO2VOVQkMRYPUfyqyxeegdfWaj5EulWk14iheV1KEsNNZRYyXV8mWE4aLJVLKG3Yy/kZN8k666znBkjQjAcVvFEiKH0ULR4cYwGThbulo2XXGe6E1GxNJLqMGmxiBImKCh9+l6e8cQ5NjNpItWLE/26m3Rr40RSUNADziQuYLujJLvxopraarLhaNg9Fb01ygzzNKw01XQW4YG54mM4Zfb34yrCQ+Z+9q3PIWTEWSOWROilRUa2ytjRENvJJVxjHIEE2aLuzOBu9NgfLLGkjtPqnUHzXRaNPJHqokmHZcawtx8H4EjxCKe2T11u1KvX63S7z91MsoMdfKXxiff/J/apHo9mMlwlHyNcgg1jmuM37rtyg5q+BSauI3f6QW5w1siOTPAHc7ejKQFj+57kQ7m3M2q2GH5NjUhRuPapMtGvKxitT3Ls8EfJZ7dpZBJsTo1R2TdDeW+Wp0otnrTWWR8pkQ8VXv+JT5NutWjaNg/tHadlaLx96HHShks3LFK+x8c1dKav3eJ/ez8AWpcz2XNcX9vLU+QxFZdj1ZPs3qyyXSix5RS5Xr2H/jDIRRUnlIhX/fQL3mqr/RS93gL3Nfq8YeaNfHirzm05h/TA+pKLnwAk7PuHvTy2YWEMdmd136Y6kCsnZOy847gukWKh+nFYSN22EAiaQX4QFuJeDguxRB2AoWaC2kDm1tCN2MkiTJO24/VTD3oEfqxNLvl5RNRDyjXWLYEjLZDQVwApGDckDWmQU+L1rEX84f9ou09ka0hgtBV/CKjZSSw9RcOMCXNxu4KrxNVl2Te4OHCyGJcWQa9DhMSMFLJKn6wMqflpogK0rdjJoq6kSYghsomQSESs9VXYfAqi8DnnQVUTOM4BWq3H2Z/bT7v1GACPNTv/9GAh4obJxfte8bHTOwT5y8Ti3GkU2+bJoQyW7GHNq7SUHhMTS7F1zw5esdCHhwdeyPF+mlMV6J5ET27jygJDYYWNbA6n12HIq6JHDma0hGcnqChFpt01+paOi05C7yJR8FXomDr6doSXXGOmE1dCPGuEfLCCkCq7IoXIG6ITdOlp8aJazwyT6FfwyiWCQCeV6LCir6G7eSatOgBKJ6Cc09GlQr0/zEw0D8DJ/YdQXNDXBUKJGE7EL4F5LUU+2WZia4NHU7cDYFirjJQv4euTbCWXWeQ4KbMPSOrWMGHX5+rOec6KSUSjRraxzHpqatCo57BNnrHeBYIw4ljxGC2/xWJzkbGxOGFwbW3tZZq9HewA/i48yrK8hq5isru1SN6tkmmn2Hv98/v2vqQQAm75cUR9iYPR9XxX7mE+O1YnXEhRGpmnt6vNx7y7SPoBV71lifpQlt1bdY5+qAG/aaA/Osfs5n0MV09j1DfpN/oE/ZDcxgY3fvYBXv2Zz2J4HovFHJ/fM0o96XDt6BZTxjaKUNk6eZSwsU33oOR++1UEVpuaUaMfOPhBgTlvnMNynUJ5hdntOueuPYSj+qgjmyDhcLVCmB6Hyetf8FY3Nv6aCIVTPZOxoTtY6fu8Y/gLqs5nPwTOMIye+AfnJS0bRdMQMiL0rMvxzmYQE1Gn3yUwHBTfJ9nv07QTSClxvSyG2aYjXIalZDPKkn06LMTLUx1UkLtaHBbihRlKep2+aWK6bURnFYi9kJWwhhps4amChiqwpIqrgtrLMqxLKorOsIibBNUgXtd29dMYelyAMPoFkt0aW9k8hmbSES6eqpCr1fDVAAVoeAkWx+Px5QOFjicJlR7pwMZRGjgyQiJYyw7TMQ0yjVjyJsNJFFXgjXRZ7ibA70Dl0vPORTp9nGbzSQ7lD7Bc+RyOqvDoc+mQp2+C1jrU5l9oir+msUOQv0z87h9+nJaa4awzwp7gIm56gmbiLOEtX73x0jv4ykCfGMfudOnY8fbarnWB8CIUu0k3KpLzy2ylbASSoK+g6ykY2KutqOPs7i3TtGy25Rg5YxWhZokUSc/QKdWr9PUqk4Mtrg3bAhn/fdY3QOqcaw1hEG/5VQqxrjmxkEBIQTJZpxnFXc0TOYtiUKWipKjGCgwuaSq7Brq203viatnTThZGeg1TCNpSQcmo7FucY75wiBVdIxNsM1WpU0/tp2e0eErOMmYOEvUGjXrH6xdpkeTEpkPGW2ErP4aeqaM93agnQi4tr3KkeASAU9unLhPk1dXVl2KqdrCDfwIZBgxlVM7p4ygyZHitgptOocsmhYmpKzu4/W+C4n4KTz3IcavO+NB1/Mf2LFYn5NDeezi7Z4gHqm+iVza5+XWnsa4y6FgOB9cr3PrwPPvv32bvgwscfugMN37+cd78ifu44777mVhfpmqb3LNvijNjOVanDnFNYZsb1SdIaAHluW+gd/EcaxM2pb0h56PrECLiidQi1zdmeVIUsRSXq7YeZv9mhUqhyHp6mJvFZ6mOKfgrBhOeh3rnf3zB5rwoCtjY+BDnXJPrxl/Nx2sRtqrwDU/rj902XPg4HHzbP+nlcRwH39Cxwy4dL0E1Ff8utV9DkZDw+rhmCsX3SLourWQKL+oh+2lsvYUnAvICVmWWEXUbT3rY/jCtSBBEEKiSlLKFF6VJ06dnx2EhiepFXGTshRxuE2FguT7rZlxFjr2Qh8irkk1dY0ppgpAku2UiAvLBMPYgQMT3s5et3jRVQQpJ2zRIttu4JiT1JDU3QViogqKS6AXUPRNHdkh7aXSzfJnAzUdjCFWSGjhidJrxQq+OdVltZuOD1k8+73xk0scJwzbHMkN0/Tb7E4KTz0mQb4m/Ln7+ea/5tY4dgvxlYmSrQ9N22VBH2FVb5o3Rfnrl84wc2SHIr3QY02PY3S6dQVjIbNnEcyXC6hIoGrn2M17IXkvDNtO0ZeyvOaeOsau7QtOyWZa7KWkLKEoBJRJIIRhya3Q6NsVgA0VKFpIKNSP2XC4EcdV4rj5FkQ1CoVEpxil69qZEUQIsq0UUxduUOSfPeLTBXGYMPaogkaxHPkPNUYpRmYsTMwCImoIMBVZ2hZyiEAGVzDD7FudpJ5IsGgmm3C5Tfgqpxu4XZzXBxCBRr2l0kUIw7ccvgGJ7hJRaJlQ1tjM1dD/eUlxhhPUzn2dXZhe2ZvPE1hNYlkWxWGRlZeUlnrUd7CDGwmd+lV2ZLo/lDfZyDn9eYdme4epjo1fejUdR4NU/jdg6w8HoRr7b+igbE+M8ePYgquWyd/p+Pn94gpPbb2L7tMPswQWuvvkinckJlkrj+KpCtttjtFYl067RNAVnRvN84vAU9++doF+Y4N7bvplv6X2aVxkPYKsB60vfSOvhh9nOOxy6vsz7e/8KaVW5kLrEocYellWTxf4YJ/w5JjaWGa+0OH3jMZKKjzW+iqJJ9pTrhIksHH77C95irXYfvr/N51ohb9n9TXxwq8abihmS6kBeceFjEPTh8F3/5Nx0Ok1fU0iGHZqBeVliQadHItIxw4B2MoMIXBKuR9tO0wlaaN0MttpFUQKkErAqRhmhRktIjGgMKQXVUCATIY66BSi0wzyebWB3O6S7DTZlxIhXip0s9F1Ybo/VhEoOh8iwcLezpFXJsqGSkgG6E5BuNmgZXaywhB1VQI2t3tRgi9WhkWes3hIWiV6PUFMwzRJVz+a47152sohQKHltkmGSUK/RUlU0QhabM2QTXaSmYHgu29s6IpIkh3rU2hmkosHayeedj3T6OPBMo96QqHK606MXRv/04OL+WF+++LkXnOevZewQ5C8Th7UGZ8di4jKyUGVSmuTrpzGnruAW3Q5eFhjTY5heQMvRiVAYbtg0+nHhRLcr5Cuxfmt1aJhKO0UmZVOVsXzhrD5GJmyDETEvZympCwg1hz7Y4jNln1ozB/Yq492AxaRCqOcJFRcxWLBWW5NMqms0zRQdRxAqOk6rih+YCAFZTaGvdEibRQrRFqvOEJNry7RUj64XkGzvZVZcuuxkIVRQ13Ws3CJTg3F8NnMz+5bibbQ5bZjhMCRZjMg3NIRU2NY3GTJj+7ggKuM6WTKuQCHClxNII45nnbd8RKRjqiarjOAvPoiqqBwuHubUdhweMjExwerq6rNHnO5gB19hfOje+0hHeS4m8hz0z5CqNFG8MfbfdAXcK54Nh98OQwfIP3EP+xIG1+R38ztDPawlnaGJBZzMGvdeNcL56K2s3JtDT4ZcfeODXDd+mlzYpZ60uDic4+xojsViCjczjD18DY/c/s+oTEzzn+b/A9cWziMwWLv4Flqff4BaxmHXrRv8n97P4KWWYmmFnyEdJHkynCKvtji+9nmOrW2xvmuMjeQQr1Y/RWVcwVs02dvrot7+M6CoL3h76xt/jSc1thihZx2hGUS8c+QL5BWn/yZuBpu66Z+cm85liBTIhB0a0sLVLfoJoO2TlBZmFNBwsojIxfZcAt2gLDqkO1kgtnpriz4VbZJhUaWmKQRGHtvTqIYCNeOTVLcBKIeThLaO3e0irQIVIka9YdRgi8CYwvBqzKUUClEGVJVuM40h4JwV0yvVjjCbPbasgFCOkfWXiGyNRRGRkB0q2RzhwNHCTSQxggDDdQnNIWpegoN9n46TRGlvIxDkenFVt6eEVFHJiy5LrTFSqT51QrK1OhuNiISnks+6SAQ9NQNrjz3vfNj2DJqWQfdXSepJFPc8gYQnny0wRFFg6mZY2iHIO3gOrKycg0SKU4UsSdlGWzLY0mpkjqqgGVd6eDt4iaEVbBS7APRxrRzprsZ6EP+XMpwthipxU8RKaZStZpZRq0u63SPhdTmTnAQgLVpskKGorqIoeZSBxVrX1Glu5PCzq0x34FISkmoRaWwTRRqW2qXaLzBjLbKdShPoPfpmFqezSrcZ2xmNmBFnMk/hhCOkerE2LbteYzMp0HsKZnOWWeaoJrO0LBvFB3MhwMotcLAbk9R77GPsXY+dLJ4yY0mEPrTAyPY6iWiEreQynjEGSJBtGslp/M0ee6IVFpUJtrvnsHotFowhQq2LGqRYZIJ0NfblPFI8wtnaWbzQY2Jigm63S61We+knbwdf95hTD3A6isnwZGUD3QxRPY/xA88fbPGyQVHh9n+L2D7PYXkr7+D9uEPfxn/tFrC6IVft/wye7nLP4TTnx9/M3McmaCw55Pd1OPjWDY5cV2X/pKQ0MUbvwCFW91hYic/wU/M/zf8rf4kjqQpb/YOs338DnUcfYquQZubVG/yJ9++oZ1eIlIBzRptj/SEuGAkqbp5b6o9wYGWdRD/gyWuvoaQ0CCe3EIrk4GaFwEzDNf/sBW/N86pslv+WB9pw17538oGNOiOGzm1Ph4N4ndj/+NDbnpVsZ4ZiIp2XbeqKgRalqKcFtGTs9iBDaul4xyrVj3e4lg2XbDc+7+mwEMEIY6JCUxH0rTzprk41EGjpEOvpsJBwBpkQ6EFAaKZoyIBRP4/qbxIakyjBOuczKpmBk0WrYyEELAxkH5YRIpoRC09bvbmXkLbKkogY7sfEeFuEGIpFLxFb2KWbTUJFQSLIdgzKGQ3ZrZJRUii9uPCiIBAyoiD6bPSHMDMuFQGZeoNy4JAkR8GOq8HrfSX2Qn6eRj0hFNLpYzSbJzlcOEy9/gDA8+uQq3OvaD/kHYL8ZeC3f/djtFSHM8kJ9nkXEIVd9NRTGDd/05Ue2g5eBmg5EyVZJNGr0LOKOL2I+WjghexskWmpGFHEyvgsnVaCmf4aQw2VYnebS6lYolCkRlPopNVNUJ/2/oy1aO2NDL6zzu52xHJSJaeWSIkllCDBkIidLEYS59lIp5FKQDtZJNlepVOZJAhVhqwuTyXOkOhOUuzHi73S9FjNGdi+htuaZDqKye+pfQcQLhiLAtXsMm40QMJ5LctQosn41gYPpu8gBBL6KqObF/GMSbacZRbFcVJGrI+uJQoEzT43tE/zpLILvdsj01pkIz2FluojOg5tkgy7i/S9gKPFowRRwNnqWcbHY/u7HZnFDl5qhN0KI6UeZzIGKdkgNd9iOznJwXENddD4+lWBg98IpcOkHvkQe7IHuDO5zbmhA5y6UESakpt3fYyaCp+fSvPoa46zcf4Ycx8tUV8okE81OTrzJG+Y+DDfn/5Dfsr5CN/tPM5Rq0bLm2Hh7FuofaSPt3aB9RmHyVfX+NP+f6KcX0KXCo8ltrmhPUHdavFw8yiHw0WOLz7G3s0al27eR0Oxud26m86YxF8wmHX7aG/67y+qOLS+/n9B+jzQtbhl+h18utriO8byqE9LW85+FIIeHLrrWc/P5LMAZMMunUGaXjUloClISh1VSGqpQaBItw7AmhGS6ca2loYZx03nscnLDi1FEmoJ8i2NaqCg2ZJQ6aDgsx2MoyTjXTupqvTCHgmpU+z7BNoQkVxg0VFIy5jcdoIBobcFgRQ4mkfkKlyyXCQWh7qbSFtjK4qYjbk727pKSi/QMmO5Xq5apafG5DbsmlwseoBkEhPXdfFFgBUpZEWfXBThS41qsUhr4GThCx2VSXRd4Gb7LHZM8NpQufi885JJn6DTucDRwl7mq48wbuo8+mwVZIDpm+Ovr2CZxQ5B/jIwstWhlupTVQrMVFf4Jnc37vIlRg6/8UoPbQcvA0RCQ0mVKNTKdO0cyX6HS0JFRJKEs4yMsox5bdaGJ1DbITP9VdJdk5y3zlJ2DB+NsbBMIAIUEaANXiyBImlbBtGWjpdcY087IlAUQnOCoXAJRerMSIXIK1ELfLzBelwpjKFFHiwWCAMdx6mzpm6h+Skmcz6psENLWmwW4hPOaia72jFxfnLfQSAmyABWboGEImhJgZLT2L9wicX8LpYNnUJQZabSpJbaj6f1OCmmGbeebtSLycV1jQs0cLh2M0smXKOaKyEyW+hu/CGgL2zOXTjL0WKcNPnk9pOUSiV0Xd9p1NvBS457fv8HOay5PJxNcUQ+AYshm/oejtxy4oVPfjmhKHEVuXKBg8E1vDn6vyjFd/HrBYPEBR1lpM/x7Odo6D7nkrN85HU2q3tvonx6kkt/UeDiR0dZfmwv6+cPsXbhBIuP38Lc3VdT/huX3slHqaVt/JsCuGqWD3T/H1ZKT2FFGk8kqlzfGcU363yqew0Z0eGO+b/jmqUNWqMpHp84xlWcZmWPT+gpXLe+RZAeh6Pf+oK3JGXE0sofM+dqXDP5Vj5cjVAEfOdY4ZmDTv4xZKeeaQb7R0gN4qZTMvYwzrhZyimB0hAk8BCKQjRI4nt692zTAOcLwkJaos8wAjMKL4eFlBr6ZSeLbSNBWi3TCocxknHDs1Ai+mF8vXG/AAh8scCqrZCUJkKCK+PzJ02oRyYFNa74NkW8rh3p+MiESgRMNjMoUUg5myOhp2hpAYEiKFQqeGqAAGquzcXxWO6R9VSankKkdEiHCdJqC5uYvC/aI3RNnUwzXou9wb0y2WGplY3//gIyi0zmOCA5nEwSRAG7rYBHn83qDWDkKtCTOwR5B8+Og3qTM6Pxp8bhuQa2EIxyGiU/e4VHtoOXA0IItKERsvUaXTuD5XXZDlV0P8JKreHKImNBlbWhIVLtDhO9DYwghRktEtomm+oos+4qPcukJZOkzBpSsfA1SdvSKWw1cBOb7G7FlYS1ZBKi+IWwx9dB6pxtDpOkggS2i7GThb1ooigRyWSNXhgv/EOZIhPhOgupESIjXkBXpcdIY4icrHJ+Kv43q2wpyEDByi9QEHGj3npuikPzF+gkkizqSWbcHjNeGrT4nAtaxHhiQJCNWI+8h4H5fnuShBnbFK2mWmi+gwBWGGXz9OcYtocZSgxxavsUqqoyOjq6U0HewUuOD26PsB0cp6Em2d1ZIBc2SXcNdp34KtEffyEOvAWGj2J9/vfZM/xGvk38GbWhH+GndIXsVsDQoTVGjdPU1U3a2lHuG8vyc+9Smbt1L63cIRobGWpPhdQfr9Oe26JNQGUqT+9WgXFrjoecH+VPnCnqhbPYocUZo8/xXhHFKnM/e+n5Sd6y8lFuml9Ck5KHX30bCeGxb/Qx1GyIcVFSDH20b/qdF5UcW6l+Fs9d5Z6Wwrce+E7ev17hDYUMo+ag8lxfhrm/h6u+/Tmv9zRBdkS8Nma9PJuORG0JTD0mk0YY/8xpx4R2K6FgSZtGlEZL9GiLPqMotEIHocQkcKSuU73shayTVjfwwixJJ66i6n6XoBdbyY15QyiyjQjX8BVBXYVEpNFXQQQmY3rEtmIwNvBZVvyYIE95eRJqTLgT/WFSnQ2Wh8cwNZNAenRMnVQrdrJI6Tbbro2ZryOFgtXzafoGGdkk7aXR9NhmTiPkYneapOFhaQpCRlSrMTdJlLpUmhmkaryIRr2r4uegxut4Ntpgpe+z5fn/9GBVi638ll65ThY7BPlLRHltHqwkTxVyZGSNaNOmbK6j3HLoSg9tBy8j9NEJnHabdjL2Qh7fUNDcCN3ZphuVGPLKrGbTKFGI6Eo0PUcQxQvskjLG7u4KNdthI9pFUZ9HUfJIIFBVJtpbdHs6o14ZNYq4lFKom7HOLT/Yxpur7maKFXpaklreRiJw6j1AxiRZ1YgIydolhsIyi+kRxssrdBSPjhvgdA4yy0UWRwY6Yh3UNQ0rv8jsoJLyyextHJqLt+Yu6mPkowhrpEuuoaJGOtvGGkUrJsSB3KZvZ0m5Akd2aURTeNEFAC7pKlJILNVhmVHkykMIIThSPMKT23HS08TEBBsbGwTB0/GuO9jBVx6Oo3PWiPsAxlY36aYLDFltLMe5wiN7FigK3PGzUJtnX32I29XH2W071Apv4w8qGnYv5PiJs5hWmVrwJKGZ4nD9Zj48vZ/vv6vGf/zeFf7823s88nabc2/OMn9HgcduOMRvTr+e/zSW5L6JhxgPHQKpsilVDns2CWeBR7QZ5hqzvH7z03zDmSfIdPqcfeNVbOHwZuNDrM5I+usGr65u4R94E8w8e7X3H2N+4bdohQrJ3G085Q9R9UPePV585oAnPgBIOP6u57yGpmkkVJNBHxwJP0NlEL5nE3/ATvX7SKGjuT52r0fVNlFRaAZ59ESXrugzHknWwxwpNU7gS/ezlyvIHV0ho63jhXlKRo2+aWJ3G+iNiwRIxrwSql9GRG20IGLDVEmRwNdV1OYIRU2yZqjMqvXY6q21SURIIRgmqcSk3fOzqN4aC6MT6IP0vLZpkOh28U0Nyxym4iY5EfQJ7Rx6pwUIRvsddKkT6U2WhUVedFloTJF3OrR0EUdOVwNMD3K5PqDQ1164UU/Xs9j2LFH/IgWrQNB9CoDHnlOHfHMcQtJ7ZfaN7BDkLxG//tsfpKXanE1Msa9/kXx+Hz33JIXrX9jeZgevHOiTEzidNm0n/rS+e10h7EtEskVPZsl1N/BVla1cgX5Tx3SyNKK4onpJHWOmt0rTSnKeQ4yoCyhKHm1QwXCCFtVmjjC5wnTX56KjIo0iodqDUCIIWG5Nskufp+Jk8Kw+nu7gtNfoduLtylEd5lPnSTOK028QKBqllTKbNmg9gdmcYReX2HZycaOeB9Z8gJVb5GAnXrA/Z+znQOUSeuDzhHUtAEZxjrHNOSw5STk1T8vagyIiwKXuTNNbqnM0uMRZdZrtzhxOu8yyNUJkthF9h1VGKTSeQkrJsaFjLDYXabgNxsfHCcOQjY1XbuPHDq4sagufYzLv8khBZVrOoVzyWTRnuPbWr+Lixp47YNftqPe+jwNTP8x3hr9KLfPNPFLcz5k5UKXkDQefJHIUNvzPMrm0zIhv88aNVzG98U5O8yreXyrxvyYF/99ol88WahhawIn6QSY6U5QR2JHBiOIzMvQoDyj7eGL7CN9Q/jTveuKzFNtdyndOcMrex23ifhYOBCAFRxcqRJqJ/o2/8aJuo9F8nGbjQT7VUvmXV/0Qv75U5rBj8arc4INJFMHJ98PMbZCbed5rpawkxiBxT/NSl8NCrCCu1Kb7XQIjheoFpLpdak6KUIZ4/RyW2aIt+pSEwkqUp6SsEMnoH3ghe0KSUTcJpUVWBnScJMlOk2xtgTUZMeYNowXrBNoukr0uywmFnHSIDBNvY5iUKrlkaSREhJ4OSNUbdPQuiaBEIlpFKrCGghlVWRsahoGTRT+RJOG6qEFAqBep+xb7+wGdVBLR3kYVGrlB4qirBNQjnYLSZa1XIpntUUbGThZdHYccpWRcbFjti7hRL3z+4kM6fRXN5uNcNXSMte3PoAl4sPEcMovpmwEJSw+8wMx/bWKHIH+JGCn32Mp5NJUM09vrvLU/ibJ0ieK+11zpoe3gZYS5awa706WViiu7M+UEnX6sVdMSdQrVOIxjpTTKdiuNk03THBDk0+Y4lvRQDY9FRiipiwg1jxHG/y09Q6GyXiLILrGnJTiXkmTVYYSxShQaZLUODbfAHuc0q9kckerSTeRJtZfoVCeJIsGw5fJk8imSvUkKvVhvbNS6rGQNHE/Hb02yOzoPQvDYwSMIb9Cop/cZsqsIYE5Lkcr22Lu8wOdyd+ADCWWNqfULtJK72U6uco4TFK14Ea05ecJmnxtbpznHJLvrCpnOEhv5aYxMF7WTJkCjKKssb7f/QWDIxMQEsBMYsoOXDn/zh/+ZCT/FGbvAweAMme0GRn+Mvdd9FVtzCgGv/8/QqzN87jwnsiXuUD7LQuHf8XvFAspZHxIRdx04iVKY4O8nlnjDR/+Wg6dPk+sHHOgWuaFynJs3b+aGrRs4XD9Mxh3CR6AiGBI+xexF9h78DH/a+AYeLR/jWxY+xPc9fDeFbpf263J8unAL+7iEsn8VM+Njn4mY8l3Ud/7v2BP3ReDS/K/TjQSkX8W6mOZC1+VHpoaf8Z2e+3TsjHDiu17wWqlkisjQMSIX10teDgvR3G3USJB0e/StDIrv4vT6NNI5ekEL0c2T0usEIkATIStihElli5YIMeUkktgLWSQi0mr8Qb0RjuA6FqlWC0MkKBMx7o6i+mv4xl4Mt8KljEpepkFRaW1nMRU4ZQ9cjZIhRr1/2eot559H2hrn1YixvkekKGzLAE0Y9BNxc2G62cRTBSBIdSw2Myqys01Oy8DA6k0VEVn6FKIAX+rUikUatkmuWqMpHExtD6YpcW2f+ZYBfhfKp5/3uWbSJ/C8ba4r7GK1NcehpM799fazHzx+DSh6HDv9CsQOQf4SsV9vcnqgPy5dbOAJj5HhDTC/CrfodvCSQR8voKoJXCPCVxMU2habgy06w9liqBw3UCyNjLPdzDKhNMm3PNK9BmcGThZZ0aAmLAraEkIZRN097WSxlsVNL7O3JSkndFLqGEV5CTWwmRQBgTuCLxp09biSUs2PYbl1gpVB5LRTY1lbx+gXmcq0SIZdmmGC8lB8/BnNZE871uydPBBX0PSlZxr1kkKhKyHMJjl06TxrhXEWTIOSV+dQJaTlHEGKiEfUHDN2vM1WteNGvau7K4SoHCoPkxZrdJIpetkttEFgSFXkuXD6IY4UjqAIhce3HieTyZBKpXZ0yDt4yfCIvIoz0fWEQmWmsoxwdAxZJzsyeqWH9vwYOQrHvwPx4G9xcPgH+Bb5x2Q1iCb+Cz+Vy1B4qo+SDHnb3kcYsSf59+/cTWlxjrf/1Qd5w8f/htn24ySS22hmF81skXW2GMlfYnbifq699q+p5ODnH/tJ2hspfuH+X+V7Tn4GR+3TfWOOvx16PZOsM7vrFFGph3vO4NbGNu5V70IcePOLGn67fZ5a5ZPc01J5z1U/yvuWykxbBm8Zyj5z0AO/FXsfP0s4yD9GKp3CM3RSQZuGZ1+uIMtuB1vqmKFPK5lD+F2cvkvTydAKm9itPKqIMK0OLdFjS5thUpSpaILQGMXyVLYDgZrzSQ5iqNfDWSJHxe71iMzsF1i9rRFYs4hwgbM5jezAyaLZjgsm605MsWzDJ2oI5qwAX04y2TuLdHQWidjXjI8payFpo0Dbis/NVWu4ysAfuWtxZtgFJOOhTtcL6St97EihoLRxBkEjS+kx2pZBoR6vxX1vFITAn24x1xjIWJbuf97nms3GOvz98TCYUGqcbHXpPltgiJ6ISfIrVIe8Q5C/BMydfRBpO5zOFSjKMm4rQ9W+hLxjx73i6w1awUJJFlHDJv1EkXRXYSmMyafulMm0TKwwZGVslm7bYk9viUJLo9TZ4HxuFwATURlPBJhKB1WPF9hAjZ0s5IaKm1piTzv2r2wnhsn4awgUDgQGMnQ4185hykGn9nAckZucsxBC4jhVmmHcEDJcyDIdrnAxMw5qXNlexmWoMcVYtMK56T2ARNQV8BSs/DwjKEjgYvYAh+YvEqoaC3qWPa5LSXew/KH4OlqTsacb9fQmkaoxMcj70P0ZDGMZgDm7jxom0BSVZUZpXfw8juGwN7uXk+WTAIyPj+8Q5B28JJBRyOhIn9NZA0v2yM9VKFsT3HBi4koP7cXhtf8OhIp93+9ydPZf8M/CX2EuGuXqA/8v35fLMXq6i5oKuPPY53hNaPEfvu0Iv3/17ahtuP7DZ7njT/6em07ezTX9j3Mw+2kyqfOcrB3kN+7+IeY+cYh//fk/5H9//Be4amOFzJ4Om2+Z4kOp1zPJCvt3PUZ3oklv2eQNG2t087sw3/prL3rop87/Z3oRJApvYV1M8mizyw9NldCUQfW4cgku3A3X/jPQzBe8XjqfxdMUUkGL7cigb5i4FsiOhyMtjCiglskjpE+630IqKku6S7EVy88SVpum6BGKUSbFFjUFuokhcm2drUBBywUoogFEbIVTiAEBF4pBN+rHVm9uSKgWCOU55hyFXBQXyNoDP/xsArqRRkHrghTMmRuAybWdFiRVGmHE/kYKEYVsZHMk9SwNLSQCitvbeHqArgi2+0lOzcQ66UxfUnN1LNEkEzg4+jaRAhoh571RbN3DVkCJQrbL8XNMjrVptx0iMwPLz0+Qk8m96HqOhL9CQkug9k8TSHjkOWUWN8XaZu85fv41jB2C/CXgD/7wXlqKyXlrmr3dOfamD+Ntn2LyxNuu9NB28DJDKyRQkkNkWmW6iQJOr895NJCSZGqRMMrFVm8j4+gtn73dRZxegrQ/RzVToKrk2esu4WsKDZnGMVtIoeFpES3LYGi7Rl+vMtuOm+DmHI2WFv+3Hffiru9ztV2Ms4KrWlSK2bhRb9NFiAhN80moChJJLjlEKYob9SbXF+koHu1+gNM8wF5xjoXRMSQgFNAWVRLFS+xxY5Z7d+p2Di7GzXZP6XtISomYWGF8cws7KLJtL2JZgzdIVKWRmUJu9JiKNlkRk9S6T6L7fS7qWUK1hx5lWGSS5OYjABwvHeeJ7ScIo5CJiQlqtRqdzitvwd3BlcXjH/4FjugBD+aSHOQptAWPitjPgZu+iuUVX4j0GNz6r+D0XzMd7OH2DNwm7uODvQN844F38z3pPGNPdDC1gBuvvYdv8dusHw/5F29/N7949beyaI0x8rjLzJ/67PnFiKv/W5P3/H9/x3s/9mv8u4f+D9dtn8eZdSncFfKpa+/gU+qtHOYcYwdP405U6a+ZvH5+FS+Rwf6+T73oQKx6/WE69fv4bDvBv7z6X/Nf5taZTRi8a/QLrN0e/J04FORFBI0AZIpZAPJhi6pioEfZy2EhaZlEJ2QrF0s/cgM7ywUrJN8eAcBKtGgqPfIkyMsODSUiUi1GqzpbgUDVoa4aOEqFWjCG4cRe71KDwK8DMO6XUHCJonnKpkAKDT0S9BQgUtltRmwJ87KTRU/G0rGD7igJIy5c6P0RnM46lyamMXWDQPi0LYN0o0nX1sgYWco9h1mnjTRsrFaHbmgw7jdwfAfXKLOqJiiIDhdruymkOjRVyNbrrKz7mL7CSL4HCGpR4gUryEIoZLPX0Wg8xPGh45Qrn0YBPvdcMovpWyAKYOXhFzVvX0vYIchfAmbqfdaLLh3hMF3e4LX9Ieztc9ijR6700HbwMkMxVdRsidLWJm0nj91vsahoGL7ESq/gySLjwRbLQyXSnRbjnU10mQPmQRUsqFMc6MxTtx3Wo92MmBdRlCISga+pTHTKtFopMiyT9EMuphTaVpZIBCiDZovFxjS71EWqdhY34eIZKVKtFbrtQaOeKVlOzJMR42Q6VSKhkF+tsOYIzK5KorGH3Vyga9isFkdQemBdCrGyyxxwQ5DwgDnFVLBBrlXn/tQdABjJOSbXThPqM2ym5llWTmDrLhBRS47jrjW4pn+WJ5RdhL0W2cYCq+lp1FQfpZOiSpaJ/gXabsDx0nE6foeL9YtMTsbuAsvLy1diSnfwCsafP3aJvneIsp5hb+ciadEl0Q8Z3bvvSg/txePWH4f8bsRHf5rD+36ed/NHpGjzt7yVO3fdwbuLRexTXVJ9n/3XneTNuSf4JmUJeaTB7772bfzom3+KX7vhm/nLw6/m/r1HOX9gitY1eXJvyzP27hRnrj/Mb1vfyhIjvM68h/DoBbShMr1FkzsvrhIYNonvv+9F646llDxy+v+hEQr2zv4A97YNznb6/Ntdo+hPV487FXj0D+HwN0H6xUldng4LKURtOopJ0s9SzgioKSSQCE2j4cTBG5lOTJBXLEj1S3hSx7B7NESXCRREqNBQYwnBeFVny4+p0bZpkdXW6AdFMqkWAFrYI+zFO1yT7ghKsI0SDqwsDUjJBH1doHdKjOkRq7rBXqUKQmJ115FETLgTJNV6fOt+Ds1f4uLENOYg6a5lJ0i1W4SqgmpOsOUmuaHfp58poDe34vvudBEIXM2lHJqUlDarnRGsgsemgMJWhdV+grQyxrATEighl5oCmquxld7zIJu9nn5/heuLe5ivPcXBpMH9jecgyJPXx1WVV6Af8g5B/iIRRRG7zA6nRuPAg/z5Nltqg/TVmbiRYgdfd9BGx8k0G7RSGRQZMbqmoPdDtHSZbjTMiLfGesbB13T8lophFWmHcfPHOXWKvd0FGokklzjAqHoRRR3CGGzRJcMOW80ifmaJve2QMylBUh0jMiqEoYajtqn0h9ibPMtKPkeo9ejYRdKtJdqVKcJQYTjR45H0YzidWYa9eJuOVsBSwSDpa2z0x9jtx4l6jxw+igjBmFMQSkQ6v4QOrAkdowCH5y7w2NC1VFWFfLjFro0tKplD9PUOD4s9TCZiqUc1mQApual+li1yXLdhk/aX2M6NoOQqaP0sAELROH3hIseHjgPwWPkxxsbGUBRlhyDv4CsOJVHgKW0GgIm1VVr2CIcnVJRniTP+qoVmwpt/CapzJB7+c67e96/4/ugXudjt0y79JEdLR/iR4SLzFwOml7oUd5W55boPc3PiHDdqa9yUvsju6YjJQ6MM3zBF6sZhyvtG+Ev7OO9rfwMPcRV7xTkm999P4+gyxUwdzmq8aWEV10qR+KGHITv5ood7aen/QH+OR/1J3nngn/MLc+scSyV46xdqj+//DfA7cNtPvujrpgdR0rkobljLuDnWMwK1KjDVmMw+PaupVh0RRazbKgkstsMhdLtDU3SZkoLNMI82sF4rNTNsPW31ZijktGX6YZExfYueZZHoNUjUTtNFMu2OoQUbREoau++xZGsUZZrQsIi2RshrkguWiqMEaE5Iul6lrbdxgnEScgmpCs4pknRQZztXoO/1EAg6yRSG75Po9vAUi0CqjDVNNnImsrVBVkmhDHbYdCJSeJSkR4TC6vA4taRFsbJNIDRU9qEYgs5Yl3ONQVrrC1SRc9l4R+WgrSKRzOgtHm126T+bDtnKwPCRV2Sj3g5B/iJx732fpJ/IcCo3zES0RD8aoms8RfL2b77SQ9vBFYIxM0uq2aKZivVnB5YVgq5EJNu4IkGxsYIUgqWRMaqNFMlMjpqMCfJJYxo7clEMn3mGGVEXEGoRfWD11rU0tjdK+NklDjbhQlqlpIySVS6hBklGFQ/PHUG3NmgOjPYrhXEMv02wMEoQGKRTFRb1FYxeiZGCx1BQoaym2SrE8okzOsxWI0zZ54n9caKevhD//kRhjrxQ8KWkmS1xaO4CDSfDnJFktt9htp9EqrGW+rQumU7WAaiZsSTkQBi/vCbaMySMNaSisJZqoPspFATLjFE+fQ/jzjhDiSFObp1E13XGxsZYWlp6qaduB19HcNtlxks+j5Qkw3Id+3ybOWMXx2+//koP7YvH7tfAkXfCve9lVD/OHSO7eZv8C/5ko8Zrjv0yBWea3x0t8N5ukqsebZLv95m96hw3Xv9/2TP6GaSzwLzq80iQ5LP9XTwq99HUfJzhx3H23I15/HHGhxdR+wp7H+nwuvIGm0N7cH78KURm/EUP03UrXLj0C8y5Kt9xw6/zK8sV1l2fn987gfJ0QalXhwd/Gw6+DUoHXvS1M5mY7KWIG9kyXpb1jETpC2wtrvCmu53LXshOt8N20oq9kL0CZqJFS/SZkrAYDpFTB/Zw7gi1MLZ662mQ11aIpIkldTpOEqfdJFtdZUlGTPcnB04WB0j0G1xIqQzJDKgqzfIQlgInk087WQToFZeVZEAoZxh1TyFTOqcVyd6nw6CUkJSep2XHcrVCZRtXiaUYStvgibE+yIhZErR7Aa7SIx3p5JU2SRmv5+eNSTxTITuwgmvWB5rrqRblegGpWS+oQ3acA2hahnS0iaZoGO453Ehy8rlip2duhZWHIHBf9Px9LWCHIH+RuO+vTlI3JBf1GfY357hVP4K7fI7Jw6+/0kPbwRWCuW83TrtNIzPwQt60qfVACInhbFJaj7em5sem2KxnGU94OJ0ejtvmVDomlwWlTk0Y5LUVhBovaJKIVsKku5TGTS1zoBHiqgqhNcVQsIgidQ6FGtLPc66Twg6qSGBjOK7uJC9aqGpIMlmjO5BjDOeLTIZrnM9OYfubRESUgz651mFmuciFyRlAQiQQWwaJwiVmBrZz9+Zv49BcrEO+oI8xGQRo4y6lSoQeWWwbaxTM+GXls0XPKZDuRVjSpRVN0QtPg4w4p+lIJcBUHBYZR1l5ECEEx0vHLzfqTU1Nsba2hu8/S4LTDnbwJeBvfv372OMleMIpcjg8RbrawnaHmL7qqyxe+sXiDT8Puo346x/gwN6f493JJ9jPef79xTI/dvP76JBioTjEO0ojlC8FHD/ZYLjVY3LXJldf+3luufVPuPbEBzh27E85etVfcfzaT3Ni/xNcNbZNog+jT3i84cl1Rvt95m7+AUZ/8CGElfmihviJR9+DKj304e8hMmf53ZUtvmuswLWZ5DMH3f+b4DbhVf/6i7q2aZqYqoGlxUTb9rOUB8Ozo3hHLN9pERhpVM8n3e1RTTlEMiTo5UkZdVzhkRWCi4wwra7TxccOJpFSsB0KIluSVWOyXQ5m8ByTVKuFMItsETDljsROFuZ+FH+FJwrq5Ua9WiO+x6W0ipSQTniEDYWztk8gRzjYPU3kaKxEAddU4nfHWipJyshTs+IU0+HNMp4WoAlBtZ/k8Zm4sJLpqVRck6RSoeBlsY0ydc0kK3qcbeyimOwQGiqJfo+11RA1hKFSF6RCR8u+aB1yq/EwR4tHqVQ/g+B5dMgzt0LQh9VHvqg5/GrHDkH+IrG732Z+VBAKjcmlMgcDmyFlHvEi9Vg7eOXBnB1F0RJ4hotrZCi2LBYHpNJMbzBU0dAiyaXpfbQbNvt6y4zUVUqddc5kdwMwEW0SigAhfHQjrgS7uqRhGSTXXPrOMgebMcm9lDZxlfjvs4NGvdPb+5iR8/Q0h2oxiUQhXe0QRQJFkaR1lYCAvDVG3t9i284ytbxEVfcJepJEcx97ucBqfhhPMxARmJdCEoVLHOnFL6CPW8c5snkeLfB5OHEjAEbhEpPr5zHkJJupeRrmPlQlBDyqzgzuQoVjwSVOKbM0e2tkmuss2eNEiTaim2aNEYaaTxJFkuNDx1ltr1LulpmamiIMQ9bW1l62edzBKxv39g9y0b8BTxjM1BYJk0mGrCbGwFbraw6p4Vhqsfow6v2/zYlj/5MfV/4XiajOv5nr8vO3/wbbfkg6PcMnT7yJ78qUKC8G3PL5CkefajK91GWk3WPEdRnq+eTXAqZO97n+gRrfcGaDPfUmj04dx/3RR9n1+v/6omKkvxAPnH8fVu8k59nNt1710/zYmSWymsbP7PoCjXFrAz73vrh6PHrsi34E2UQaTddBSvAcytl4rTLdTRQJqX6XXiKD4vVJ9fo0Ujm6QROjncVQPHS9T0fpsabtZpdYp6oKfHOEpKsNnCw8HDVOPl0N9hKkdBL9PqGZphm55KMkGbeJb0wQyac4n1XJyZgYt/1Y4DFiQUMalLQ4BW9ZXQEUjvcsDCvCj2CiO0qyu82liWksPYFHn7ZlkK3V6SRV0kaWzb7D3mSLyHSwWi0CqTLdq2GFFq6xzSXpUFJazDWnyeS6bCoRhfI2i3VBWhYYT3tIJAstGaffdavP+2xz2evp9Ra5cegA57cf4WDS5L7aczXq3QwImL/ni57Dr2bsEOQvAmHgU7IFTw7nMKSLeTFiw9xAv/PmKz20HVxB6EM2SmoEq1+haw+T7kaci2Ini0R6EbwCk26H5fFptEbAvu4iqV6SZDBPN5NiUx1hn7tIzzAoyzFy1iZSSeBpEV1TZ3dtlXZPpeSvkwhCzqRVWmYWSYgaBkDEXH03+82LlFM5XKuLa6ZJt5boNIcBGDdDzmaeJBNOkm3FC6Oz2WA5o5HuaCj1XezhHJGi8sSefSh9MC+BZrUZtiooEs5qabLZLgeW5vhM8U58wBGrTK9fop7aS9Xe4ElxNcNWvIjWklmirserG49zhmn21xTS/XnWi1NY2TpaL0OEQk52OLe6zYlSXMk7WT6506i3g68opJSMDvd4IqujSp/hixtsJia4+TXHr/TQvjwcfSccfjt8+hdINBrcfuy/8hP8d7bdPr+4nuC9t7+PtfY6i70mv3TXX3DmdT/Ju/ZfxX9TUsxvS0bmWxw9X+W689scWq6RqPd41EzzwavfwfaPPca1//wzpAZ2lF8Mzpc/x/bSr7IaWHznLX/Cf5/f5FS7xy8fmCSna88c+Omfh9CDO37uS7r9TDpNYJokww4dN8nWoIIs2m3syCAReDRSeUTQI9nv00mmqEQN8s3Ybz6RaNEUPQIxOSDI0LVL5NsGW75Az4QE0sUULbaCaZTMQIOrq/T8WLM8446g4BFG56gbCp6iYEQKXSERoc4uM6SsmMyqcaMg7iIAu70pUkpsjem5JVR/kYuTM5gybtRrJixSrSaeoaMZ42z2HW7puLSzOdT6GqrQyLdiHXKgevghlOjSDy3qpTyVhEmpXKaJjWUcwkgIWoU+Z+opQL5gU10uFxdBjjo6oQzZpTd5uNmh92w65EQu9ule2CHIX7f4k7/4C5pGiqecCfb6FzHyu+j7jzN+4zuu9NB2cAWhFSwUZ4TS9gbtZBGn2+KiqqMFkmRmHk+WmAy2WSoNk+60mG6tgBhCRpdAU5hXYieLipNmXh5mXD+HqpRQpAAhKLoVtpol/Mw8B5o+pzKQ0McJzS3CwCCrtdjuldiTforlfBapBDSdIVLNBdpbs/iBRjHZ4gn7SZKtWca0TVQZ4HcFy0MGulQ4qznsb8UavIeOxUTVmHtah3yJlFDoAEE+ybHzZ1nLj7Ngmox7DQ42dLr2YRCSh9UUu5IxAa/Y8UJ6tbdFhMLh7WmS6hqeaVFLV9G9uMlmXQwz98S9HMgfwFRNTm6dJJlMUigUdnTIO/iK4OIDf8IRXfJA0WI/Z7HnO1Sjg+y59rorPbQvH29+L9h5+IvvI5c8wlsO/wj/Uv4aDzd7/G6lwC+95ldZbC7yk5/5Sd6+99v4y2/+e/7193wO7dvezz3v/HU+8Pb/wZ99y//knu/+E4IfeZTb/tUcb3vb7zH2JRBjgNXGJR45+c8BuOXE7/FIR+c3l7d491iB1xe/QKKxcQoe+z9w3b+Awu4v6Xdl8zn6pk4qaFHzbbqmEnshNwPS0saIfCrZPEIGZPpx494lo89oqwRAItGkKXqUsBmSLWqKJNBTjFU0tgOBosG2ZpPXVmgFoyQzMSFVIw/XjdfLWGZRRvXXEVKyaihknnayaI0zpkuWLY0Z2UA1Q9KNdQLhMuxNYSvLSOCUAim/ysrQCHTiAkPPyWD6Pna3Syh0Qqky1rRYKGnIzhYTSgav2yMQAbaEIaVDPop1yJeyUzQTJkO1eC1ut2JrO2W2yXJtCKnqL0hmHecgup4jG66jKzqmewY3kjz8XH7IM7fB8oPg97+kufxqxA5B/iKwee8ylXSPDXWU3dVl3tnfi7J0nszE16iGbQdfEQhdRSuOU6xs0XayGIFLv6dg9UP09AYdOcaIu8J6xsHTDcK6gpIaoR7G2ran1Gl2d5ep20nOyr1MqOcQ6hB2P660BLpgbWMcrzDHwabChZRGSRmnoJxDCxymRYDfH6chegQirj5sDs+gRR7a+RxSKqTTW2xQQw0cxoYNpoM15pxRPCdejOeEy0g9Dgx5cvd+QCIaCvRUEsWLjA8CQ57MXc3Ri2eJFIULepF9roeTtci2UgipsKaXGbfjF1FHrRIYFmORgkpI5M8QiYsAnDdCQMFSLJYZoz/3eXRV50jxyD/QIS8vLxNFz1Kx2MEOvgh84O6/I+weYsUocqB3FkuNsMMm6eLQlR7alw87D3f9JmydhY/8BMND38B3738j75a/y99V2vxpfYz/dedv0/SafOffficPbTzESHKE1069lncdeBffd+z7+K5D38UbZ9/ITGYGRXzptGCufpEPff4uiqrH6O6fJbKv4vufWuCwY/Gze76guS8K4UM/FlceX/3TX/Lvyw8X+P+z999hlqVZfSb6ftse7114n5GR3lZlluuu9l1NAw2IBgQSIIxGuhq5kbszd9BIF0lXM0LSRSODkIRrnBpoGmhHV5d36W1ERob37nh/zjbf/LGzW0BXV9HQVVkm3ueJJ/N5Yp846+wvYu+11/dbv+UogqRTYRcDVUYoxgRUICr9aEKSj8a8Y+ueg89iwCXe7MOSGr5gg6JSpx8F3ZaUVE+6NrinsXvPSahgGsS1dTp2kp7AHpam4W+V8ZVmaSIZ7PSjWWu4aoZgq81CUCUrEzimD2urj7gquRlU0RTQozbBfI2dQB3VHiHu3EIGNa6pkvFa12tipktYT1AOeQWE1N4ebdVr1OvUfbw4Ugag1zLYaxlItUrCDpBQi1iKwE+X280hwmYbXVcxu202VkC4kO6tIx2Nlp58XTmEEArx+Hkq5Vc4nj7Gdv5JNAHPfyMd8sij4HRg453jh7yfIH8TTLo1Zns9MX1urkBX6ZAes75pbdY+7zz0wWHC1Rq1sHdRO7KsIJsuIlSlK4Mkahtfc7LYqiQIxRO0nS2E6/JKcBwNh5BaY1sEyWoLKFr23h+npOozqK1EaUeWmKo6dFUFy+wjaS0hpMoRywdugBuVHAl7HReVrR5vMlh4SaCpFj5fAym86kIqnqHP3uBufIDe7QU6wqbcsQhVD3JQ3GaxZwBHCITiuVkEUgscute8/AfBxzi6dgchXa77juGTEtG3yNDmAgGnn+3wApavD0W4IOuUIiNYywWmnBVmxRDFxgy+dpUlM4dj1FA6UVboI164ipSSk5mTzBRmaNktBgcHabVa5PP5N39B93lH0TVT3PCNADC0sULdl+WRU396q7K3POPvh/f+Q7j+a3D5F+jv+wH+58lH+F75KX5nr8rP74X4rx/5RSJGhB//wx/n5278HM49z91vFS9tvshvv/AJJowm8f6/ykDf9/GXby5hKAq/cHSUgPpH7pMXf95LpD7yL7wE/89IPOM1NKecKkXFR9hKshtTECVBQLpIXaere+8br3jXkZWARsgNsOPkMMI1yqLBoIQdJ46heDKIVD3F9j0v5JqhEtfWsWWINC2qkQjhWon03hwr0mWkPYhqrdLxHcXX2uV6UiPjeravxd0kugJXwp4eOeC3kUW4HXKx5AhTzRvIqM6Sa/NAwesnWUnEiRgpyqbEVgQ9m9u0DZugprPVjFAa3ANFI1TvULNNBu1tYt0ojm+bRTVETqlxp3iAVLzGripJ7+yxXHCJOBEGox0kkqUasHsbGq99bU3EH6LT2ebh9ARzhescDZk8X6q9+sGD5z0/5HeQDnk/s/tTUi3uEAib3EylicsCdjlI2TeD+dHvvd+h7fMWwDc+SqRapXzPyeLwmkmlCUJ10UN7ZDc9rdn8wAi75RgHKBNtWqQbe1yLedZGg3KLjrAx1Sqq7tn8dHSXSsCHb9OmHVzlYMVzdZiL6FTvTdTLdb1/Z/KTjItlKr4YtZiCpfmJlnZot7yflfVJKlqJuNZHvJnHVjTSa3tshCS+mkKgNMlBpunoJnMDIyhN8M1JzOgmo3RAwmU9RyZYZnRrjafj3mh101hieP0O9eAB9oKr3OIBkj4voy6Ee7DyNR6p3uS6GKOvLonWFthIDeOL1VGbUTqY9Mlt5ndqnEifwJY2t/K39nXI+3xLsDs1htIOL2dtMnKb8EyZZeMARx85f79D+9by2N+HsffD5/8+rF2gr+/7+EdTD/G9/Dq/vVvnf19q8V8/+qt8eOjD/OzVn+UHP/eD3Cne+XO/bdfp8u+v/jueuvwjnPQ3iff8JcZG/zafvLbAVqfLfzsyzIDvj0zcKy3Dk/8Ext4HR/989qixWAzwhoVIoZBspdiIeF7IPp+X/JmugwR8zSbBZpOtsA8djUIni99fpiKaDEhYcjP0aMu40iXWGaLuCuoOdEyI37ONKzv9tCN+opUKPi1MHpuhTg6tu4ZtToA9x+W054UMUGp4o54dv6DpamS0OtIV3PVvAQZnWzqGX9J2JCO1foKNHWZGxvDrBpbsUA6YxEolahE/Eb2HrVaY93ebtKNpjJJXEe+tVREILLXFjuUnp9SoWSEauRB7pk56d4+KDBAwjuD3QzXVZrp8b+rp8vOveX7jca+/asoPEsmQVuZarUnNfpWHK38Mcsde92e+ndhPkP+U/J//9lcoqQZ3fCNMNuc5Hj5OZ/0Ww8e/7X6Hts9bAHNqDMN2qIUULNVPXyHA0r0tOl9sncyujs9xmR09TKekc6Q+R65okG0tsZrsp6aEOdhdwlVgT2aJ+opIYdDVJDW/wURhlXrTJO2sE7RtbkdVmmYaV+niujaqsFirDzDln2M9nsDWGjT9KaLVBaqFYRxXoTfQ5JXYK0SbY/R2thHSxa06LKVMwpbOktvDZGcBgAvHTiJcMOY8HXIwNUcQQUEISPg5NnuH25lDbGka2U6BQ0VJNXQMV3F5SUszFvAqMfmgJxN5oLlKB4PTWzmirFANx2lF8+hdT5NYFTGmb13hZPYkAsGlnUskk0kCgcC+DnmfPxe/++9+jOFOnJuhDEed60QqTYxOmMzIn033+pZFUeC7fx6i/fBr3weFBXp6PsH/ceIT/ITySzxT7vLJq3f4f539p/zLx/4lm41Nvu/3v4//7fn/jdXqN/83JqXk2fVn+YHf+wTu5r/lwaBN38BP0jfyj/jeawsstDr8wtFRHoiF/seLHAs+/Ve8SuO3/Zs/93Ctr3ohx/AkCLFuiq2Yi7AEAc2Tc8WbDVwtjNKxiNVr7EXDSClx6ykiehmpdgkoNtNikFFli5LiItRBDEthy1JQkxZR1Ts/q9YUTkTD1+nQ9SWpuG1irp9kV8NVQ9jcYjWooKOjuoK6FCBh0ifZET6GhXddtK1lAA62R4l+daJeN4NqLzEzPI7f9goh1WCISL2KkBJXiVOzfRytKmymfMjKGhktilvt4OBgIkkpTdL3dgbm4qOUAj7SeW/yXqPaC0KgjVRYLaaQmvm6yazfP4jP10/QXsWn+tBat3AkvPRadm/rF8Bq/RlW863HG5YgCyEGhBBPCSGmhRC3hRB/8416rzeDoV2bjVyXhggxsrnN2VaUFMuogX17t33A6I+iBDPoVoFGqJd4A25Jz34oGJvHdVKMtissDY4QKdWZqi8Q7MRQnVnwa8ypYxxtzFEKRFiRhxgw76CoWZAghSDTzbNTzdKNLXKk7HA1Dgl9EMVYBztARmtQa/eQis2zEw6CkOST/fg6ZeylPmzLIBbZ466xgFkbIJNp02fvsG6mKCa8m8tt1aavkCQp97g2eQgAbUMBSyGQmaVHKrgSVmMTHJufwdZ07ppxDrfbhEMh4vUwQgrW9CKDQa/Du6oVcXSD4XvNI2Z3DKF6HqWzgS7CMTAUnSUGaN59mogR4WDiIJe2LyGEYHBwcD9B3ufPxTO1IWbs01hCZyy/hBWMc7hPIN6Jk08DCfiLn/Zszz71F6BRIB5/kH/0wN/if/X9OsutLu+/cA38R/nsd36WH5j6Ab6w/AU+/pmP89ef/Ot8aflL1LrfYAv9HqV2id+c/U0++fuf5P/33F/lk8EFpvyCg5M/jez5G3zs6hwLrQ7/7cgI70mE//iLn/ppT1rx7f9/iA/9uT+uz+fDVA3uzeLA302yde+WHLw3HTTarNP2J9A6bSKNJsVokrbTIFBJIoTE769SUVrs6JOMik32NKiH+kjVTLYtBSNhIWngE1W27AOoES8BdU2DVtdLeMc7AyhuDcVeRgrBpi6Iu36aukRvpRgyXVZNgwNqAaG5REvrWEqbXHeQIAtIAZc1Sa7lTdRrthooQqUWSaBISBSLdIWnjzaqJpcGGt7AEDdMvq3S1aokHB9ppYotVAJ0udUaIejvYGoqZrfDxhoojiTT0wBXo6ElXrdRTwhBIv4QlfIFTmaOs773JXyK4PlvZPc28pjnSrJ+8c+5sm8N3sgKsg38XSnlIeAc8NeFEIfewPd7w3Bdl1FfnRs9cYR0iN6ts+XfRv/4++93aPu8RdAzAZRoP7m9DaqhHJF6lRnNwOi6BBPzdGQvw9YmC9k0pmORLJZxff1UpScfuKGOcbCxxF4ozLScZECZRVFzBO816jkarG8P0E0ucqwMiyGdjDJCr5xGtYMclBK33ctC2yRoFZDARt8wAME7flTVJhAs06SLQKEnnaHf3mAmMUSitoqNQ7HTJVo5wRS3uds/jESCCtqSRiA9y6GOd7n4vciHOLY4A8A18zBR10UOLDO0uUrA6WMntIhiJhFIkCVK0VHctQoj7iZLDFKsX8Ps1JkzMjhGHbUbY4lB4rsXkFJyNneW63vX6TgdBgcHKZVKVKvVN3tJ93kHIKWkL9vhcgZM2SJzZ4u1wBBnP3Dufof2xpEcg+//daisw6e+G1pl/P5B/tqDP80v9N0kIbf4kZk8f+fmRX7k6F/j89/1eX70yI9yp3CHv/vM3+XRX3+UT/7+J/kHz/4Dfubyz/CzV3+Wn7n8M/zD5/4hn/jdT/DYbzzGv7rwT3hAW+FvZy16AilOnvhlviI+wBOX79JxJb9zcpz3JSN/PK7bn4Hn/zWc+sueNd23iGggjGoYaK5FpxthK+E9+Cj1IqarEu40KUVSCKtBuNWi5Q+yQYXMvQlzgUCFsmjgkzkGxB4FRdI1EvTndbYsgWrAnhYkpS9RsfoJRu+NsZZd7Ia34zbWHkCz1pBOC92yWQxoZGQCyzAgP0xak1wPaugKGHGb0G6VzUAT4YySti8hQzrXVIfjJe8zrWsuMSNLOehV3zM7O3TVDqoQ7LXC3J7w5BWRhku566PP3SLejaL5NljUIuSUGrPFCVLxGjs6pHb3WC5IIm6cwZinQ16s4jV23mte/EbEEw9h21UeSQ6yULrDibDxGjrkc+8oHfIbliBLKbeklFfu/b8GzAB/+hmVbyGeeupLNH0xbkT7GXOWcP2DtFqXGT63rz/ex0Pxa6jpQbI721SjSXSni68g8DUctOg2NbePnsYKTUNnK5WhUApjpPqp3HOyeMUcw5A2PqPFpgiT1f9Ho57EpRwwaSxEaEcXOV52vCpFKIHhFhEIDndMQOHK7kHGnLs09AiFdBBHaET3KjiOhhCQNAQd0SZhDBBv5mnpPnqXN9jyO2h1CJQOMskMDV+Q1WwvSgv8sw5mbIMD0tMhP2sO0m/s0Zvf5qnYxwDw+xYZWpuh5R9nJ7TMtHKe+D0dcjGUw9qt8EjtJleVceJth2h1nrXUKL5YDa0Rp4WPYbnB0l6ds7mzdJwON/ZuMDLiNVYtLy/fh1Xd5+3O6u0vckRXuJiIcFjeIrxap9WdZOjIifsd2hvL4IPwyV/2rNR++TuhVUZRdB6b/Kt87swhvs93gS9UYzz00lX+4+xT/ODEE3zxe77If/3wf+XHjv4YYSPM9b3r/PL0L/NzN36OX5n+Fa7tXmMsGOF/nzjMPx9UOWkW6Ov5HqKHP8NPrCT5e7PrnI0GefLMJMfDgT8ez9pF+J2fhIEH4aP/8lv6UWPRGF2fj6hdpdgNko96BQVZ7hKVAfx2l71EGiEtkk0vA73ja9FT7cOVAn+wTknUGUEnZNsUVAlCML6lfq1Rr+AzSGlLtO00Pf4CHcMg2CgSz99kHZeJ1jhadwnLd5xgs8jNhEZWRkFRKK71YirwStRr1AsFLNw83Aw6WHKIqfY0Iqyybts8UoihOhZz/QOEjAgtGtR8Oqm9PPWwRtyIs9GM8B5RxwolMEqefGK0WkYg6Gh1Nrs+ckqNuh2kloux6zPI7OxSlgECxjFMv6CabjFd+qoO+bWT2UTc0+pP+LwKdr9SYLrRJt+1v/5gXxR6TrxjdMhvigZZCDEMnAReeZXv/YQQ4pIQ4tLe3t6bEc43zdXPXicfabGqDTJZXOJ7rMPom3cIZsbvd2j7vIUwRw8QK5cpx7zKyclFlU7dRfjbYHRI73oTmWYHRtksJBgyLcKtBtFWhSuJKQAG2KYrbAy1iqZ71YOmKSkHfGTXyzTNLaaqDYSU3IirlH0hJC6m7QAud4sHOOq7w2YsRdes0/YliFYWqRYHcF3BgL/DldgF4u0xci1vbKla6rCUNom3dTatXia7nnbvleOnPB3yXYEQkvA9HfKuUFBSOifvTHMld4IdTSPbyXOw2KUcOY6rODyv9TAe8Dw480HvxvBQbZEKIR7ZShGWS54OObaL3okBUBYxpm9d5lT2lKdD3r5ENpvF5/OxtLT0pqzhPu8sfuW3f4Vy6xQFLcqB2l2E30+fWUQzjNd/8dudAx+GT/6KlyT/0rd7U+uAZPgA/+b8T/Dpg5IJvcz/XT7AQxfX+Zsv/BvKu5/n21NB/r/Hv4Nfec8/4Asf/md87v1/n189+zH+cT98VHmeZOcK8fijyIOf5f9yfoIPXV3ndr3FPz/Qz68fHyNj6n88jp1pTxMdzsH3/Srovm/px0xlUrRMjYhVYccxAD/FhICiIOYGUFTBdtJzykjUvGrpfMAlLqPsulmMUJ2S0mBMQsUJ4ahedTRbTbJ9r4+kqquk9GUkOmFpUolFiZWLxGslVqXDWKsfvbuI5T+G2p3lQlYjKb0EtFj1HhZcn6TpauSMKkjBorkK6Jxu5QgZbWwH4s1BfK1lpkcmCCgCV9qUAwHipRL1UBBdzbHbDnGu7rCdDiOLiyS0KNS+qkN2ySiNP6JDHqEU9JG5p0OuVT0/ZGO0ynophdT8r1vtNYwUodBBjM4CAS0AzWsAvFD+BlXk4Uc8iUW3+c0v5luMNzxBFkKEgN8C/paU8uv2SaWUPyelPCOlPJNOvzU9KSftBjP93i957+wutmiQONfzOq/a592G79Ak4VqNYtz7XTm4EWCr+9VGvTUyGxLVldwZP0yj5OdIY4Geok5PY4HV5AB1EWLSWsZWFTbkCEn/FlKYdDWXlqlzoLxMsZxA+OcZr7e5EgPdGMQ18zi2QVKrUWj1MpCYZT0WBiEpxnsINTbprA1h2TqxSJ5b/ln81RF6khVSVpFdJcKW55vPDV0yXPATkWUuT3mjX7UNBWkpBNJ36EHBkbCaOMip2Vt0dYM5I8aRdptoOE6sFgUpWNIqDAa9ak1Fr+BoOl99nAy1J0CbA2DW10VIDVPRWWaA+uz/0CFf3LmIoigMDw/vJ8j7/Jnommmuh2MADCytsefr470ffuD+BvVmMvkR+P5fg/w8/PwHYHfma98633uWzz3ycX7jcIKjQZXfsd/HDxW+ne+cS/H3bt/iZ278Br926+f4g7uf4rntW1wXD3Il/a/5dPqz/OXaX+UHZ7s8X6rzNwYzvHBuih/pS6H8SV33zjT84sdB0eAv/hYEU9/yj5jqy3p9Gm6FvPARsBJsJTREXiEouriGjlQ8L/VotYjiOqwFVYLSZKebwxfwnCxGJczZPfRoi0gpiXYGabqCig1tvyCledegLXuCdjRArFxGGmmKboesEyFs2ThaAlteZTGsYmKiuYKKlOAqTAUkW4qfSeEl6WrLuwZOtSeIaN7Dy7QwCVibzA6OYtS8Po5aJIFh28TKZSwJEkGg7OfSYAecLqNukHxLu6dDNkmLMrbQCNLhVnOYsK+Dbqj4201WlyWqA9meOkKq1NQoLD37uuc4Hn+IavUKZ7LHWdn9MmFV+cZjp0ceA9fymvXe5ryhCbIQQsdLjj8lpfztN/K93ig69Qr+sM61VJakzGNXw1R9t0l/+C/d79D2eYthTg6haH66WpumL0W2YjLjeBriQGwRrZ1mqN1gaXCcYLnFseod/J04mn0LGdS5q05wqjZDPhTlrnucUeMmqtqL7nh/pmGnxnJpmE5qlmMllVsxlR4xREq5jWaFmRAOdrufFRuMe2NQ1wfGEUgCt4JoqkM4XKAqWwip0ZNLMGKvcjM5RqS5hovLXqdNrHKCw9xkenjU0yFroC9rBDJ3Odz2YvndyAc5uXALgCu+I8RdFzmwytDmGkEnx25oEc0XRyCRskQ5OoyyWWbQ3WZODlOp37qnQ87imDXUToIlBojtvILr3tMh73o65JGREcrlMqVS6T6s6j5vV1r1HcbSDq9kVIbkItHZInvyCONnH7zfob25THwQfuRznoPEf/kQ3Prjt+L3ZAb59IOPcfmhI/zUWC8T8QleUD/KfxV/lX8hfop/LP4F/x/5U/xU4xP8q/wgz5ZtHogG+Y+Hhrhy/hD/77FeEn90fPRXWXoWfuEJUA3v/VNvzI5rMuVpiTNuDUtopNtpVhMCbQ8Cfm/XLtLuIFHROhaxapXNaBAVhXYjTcQsYikdwkJySxlhUlmhrDjY5giBjsaWraAmu4TUbRQs1q2DyLhAdV0cX4i6XQZgtN2P6pRQrXlcIVgxBEk3REOXmI1exgyXuYDOiFpFC9nE8ls0tBqpzghBbiB1hed1l0PlJl3DYNNtE9YTlO4NOslub9NV2ygCdhphLk7uAIJY3aXQ8TPgbhLrRlH9myxowXs65HESiRo7miCztctiSRCRKQYjHVwhuVsRUFyA8mtbaSbiD+G6XR5OZFmuLHA6bHzjRr3BcyDUd4QO+Y10sRDAfwFmpJQ/80a9zxvNP/u//jN7hsGMOcah+l3e4zuJtTxNbuzh+x3aPm8xjFwINdJHpLZNPdRLrN7lpmqg2i7hxCyW7GHM2mS+N4e/22Yov4XtH6LoepWJV7SDTDUWyQdD3BGDDGjTKFovobYKUlL3G+wu5Wgl5jhWdmhpGpavl5i9gkDlRMcPUufy3gSj9hwtNcR2Lo4rNGKbdaRUUBSXuCFxsEkGBkg3t6kbAQYXVtj1OSj3dMhHuEHdF2Kpd8DTId9xMGPrTLieDvk5Y5B+3x7DW2t8OfFxAEzfPCNrt2n5D7AdXuam8jAJnzeWtBDqobtZ4L31a1wSk2RaDtHaPOvpUfzRCmojRgeTQbnN9GaFB3IP0HW7f0yHvF9F3ueb4Vd/5idJN4eY82U51JnGRBBTq/hCodd/8TuN3hPw409CehI+/SPeFLvOH09wekyD/2kww2+cPMj8Y8e5dP4Qv3NynE8dG+WXj47wB6cmuPrQIW4+fJifPzLCd2bjBDX1699LSrjwn+GXPwGhrJcc/xlHSf9pSCa9BDnuetZiyU6OlbiDcAUR4VVpU/UKthlDbXdJ1OrsxlNYbhdfOY0qXAKBCiW1zp42yaRYY0uDSmSATNlks6tgJmwqrklSW2XXHsEfvycf0CR2axmA8fYQmrWCdG3MrsWdkE6fTGGbJvb2GCldcjHiPUiYEQdzt8XdiIXlHmS89QoypjPj2jy+FwTgbk8vETNFXbRpGDrZrV3qIZWkEWe9GeWDokY3ksQs7gAwWvH6Ubpqg+1ugB5Rp+kEKPUk2fEZZHd2aGJi6MfR/ArVngbTpXuWH0vPvOY5jsUeQAiNUaMDQE5ss9jqsNHufv3BZhh6T74jdMhvZAX5YeCHgPcJIa7d+3riDXy/N4SBHZuVXpeu8DGyssmwbZJJF0B5lQvDPu9q9FwQJdrPwOYqlWiOUKvCjqUSbDgYyTVq7gCDzXnKfpPNdJa1Qgp/upeus4pwXZ4JHUJBktYKFIVKSl9C0TzNmKVJikE/yjK0woscK3s+mTfiOqV7esrwPfP2O8VJDplzbEVTdM0GLV+SeHmOSqEf1xX0B1pcj1wl2R6np+1VWNRim4W0QaKls9kd4HDX24p9/uRZhOP5IQshCae/qkNWUVIGp2ducSV7nD1VJdvd43BRUAmfwFEsntVzHAh5Zv17Ie/G8Gh9mRoBHtrqJSSWqUTiNKJ59G4MgJKIc+vGJU5mT6IIhYvbF0mn0wSDwf1GvX2+KebFKNe0KVyhMra5QN2X4wOPn7jfYd0/ov3wI5+Hh/8WXP4F+L8fgOnPegntn0ARgn6fwflYiPcnI3wwFeV0NEiPaby2PV5tG371e+Fz/wuMPg5/5UuQGHnDPhJAMBhEV3QiqiejCHYybN0bzufrLKNIz+qtGs6gdupEm00qkTg7bolswdOWhUJFCqJOiAyjbLOnSiwjzsSmwnpXQVFh2/CT0hdpWr30hHaxVRV/q0w8f51tXKaak+jdBSzfKQLNXS6mdXIyBsDOZhpNwM2wjiMFCbOFU1e5FCnjEud0RxLw2zQsl4PVYUL1NW6MTxHSFBzZpRDykyrmqYWDGDLLbjvE+brDZjqILC2T0RPYVRtL2PiRZJT613TIdyIjVAI+MvcmkpYKnpTVP1pltxxHGmFYfPo1z7GmBYlETqC0ZgkbYZz6FYBvXEUefgQ2LkO38Wdd1rcEb6SLxfNSSiGlPCalPHHv63Nv1Pu9EbiOw5i/xbWeFIZsYyzY7PjnCH3Pvrxin69H6Ap6/yjpvT2KCa+qcfqugl11EME60rDJbHqevjfHDrKdj3NI1Ig2uvTUt7icPoKDwqSzDMKhQphQwEIiaJoO5YCPI7sLVBs+4iyTaXe5GFfAHMTRK3RtlYhaY6/Zx1himtVEBBSXQqKPYHObztIwXdsgEdvlavA6/soEuXSFXmuHDT3JVsZFILhqSPoLSTLuNpcO/Q8dMl2FYPY2/dLTIc8njnLqzi1sTeeOmeBIq00wESRTDKBIlRWtwPA9P+SKXsbWTca8exhGawwpvSleM4aNkAKfYrBMP627TxExIkwlpnhl6xWEEF/TIctXuZnvs8+fxHUtBnsdXuhxScg8qeltlvVJph5+6H6Hdn9Rdfjg/wE/+iXwx+E3fwj+2xOw8JVXTZT/1HQb8My/hJ897W2tf/Rfwg/8pudq8AYjhCARjqIaJobbodVJfi1BltU6YdeH3+mQT2QRTpNk3ZNq3fK3GKzmaEuTQKRGXqkyiorfcdhTveRyYivA2j0ni5JPI6vP4cgAaSTlWIxopUiqsM6CdJhsDaF1l+n6jyCsaV7o0Ui7EZBQbHqNi2nTYVf6GVW9ZLXuetfAU61JYqrXSDcvQ/isFW6NHcBseAloNZZCt21ilQo2EonAX/bx0lADXJsxJ8R2y8DWSqTtIBm1REPXiYoWN6sHiAaayKBJtF5hedlBtwW9uToChYIMweIzr7v+icTD1Gq3OZc9xvzukyR1jee+kd3byKOeDnnt63wZ3lbsT9J7Df7br32Koi/MrdAwB7tz9EeP0tm8wsiJ/el5+7w6viNHiJXL5JNeB/PJpSDr93S7/sQSuTUdv+1yc/IkTl7hdO0OPQU/mfY0tUSMFW2Yk6071A0fi/IoA75pFDWDBFxF0NfaZa00SCc1y+mi5GJS0K+MEtOm0awIE4qN1RxiAxvNqiKBtUFP+xe4GUJTHEKhIhXqKK5Oby7NiLXC7cQI8eoiNg75dptY6TRHxHXuDozgKAIU0OdUAtkZjra8z/OZ0Ic4sXwbxXW57DtJ0nWxBhYYXbuL3x1kM3IXyxhAES7ICsXYBM7CDpP2CtNilFrzNr52hbv+PmxfFdFKsMwAfcVXaHUdHup9iOt716l364yMjFCr1SgUCvdjWfd5m/Gln/+7jLWT3AhnOOFcIVzpYLoKwdj+YCfAs4H7iWfgo/+nN/r5lz8B/+lRePk/QG3nT/czpISd2/DF/xV+ZsobAjL2OPxPL8CDP+lN9nuTSCSSdP1+4t0yW90ANb9CKwCy6BKXIUzpsJ7JApCpertmM0FJUkZZswfxhcsURI2DrmTVzuBT7zl+NIfI24K2CxW/lyADbNmTtGJB4qUSmBnybpuMEyLR9SFVH7Z7jbqhUFQlEcegpkgUy88hv8uqaXJE3UFoLrG9ZSylQ397mJC4gVTgacNlqtKi5fOz220SUCOUIvd01js7WEoLRcB2M8LdA3tIoRCpWdQsk1F7jZAdRPFtcZsovUqV+coI0VSLLRUyGzus1DWiop++sI2lOtwpKdDY/WMNnK96juMPAZLzsTjrtVVOh1ReKNdfvWgxcM5rzHyb65D3E+TXoPXiNjvpFnklzcTOGh9o5Uib6yhG8H6Hts9blMDJQ2hSoWm2afrT9BZNrrneRL1QcgasHg42y9wdGSdRrnCiOIMme6jJu6ApXBeTnK5OsxFJcl0eZVS9jaL1EW55FYi2KVheHaGdvMvZgkvV0HF8Q6TteRSpcaZrgjS5sHuASfs2TT3Cdi6Mo+jEtqpf80NO+SQd0SZljJCo79LRDHJLW2wGXcyqgr9wmCPcoKObTI9MoDbBP+1iRnYY0ysICc8bfWQiFSbXFvlc+jsB8OsLjK/NUwkdIR9a52X1HLmAV2XYi2SxSzU+WLnCFTHBcFUSq91htWecQLyM3kxiodMnilxc3OF873kc6fDK9iv7OuR9vim+tKFzS5ykKwwmduZpB7N86Py+LecfQ9XgwZ+Av3kNvu1fe41VX/iH8K8OwL8/D7//t+Glfw8zvwfzT8LCU16D34v/Dn77J+HfHof/8JCXVI+9D/7KH3q2cm+g3vgbkcqlaRkaSavIhjTR3RhbaQ1lRyGEje0zafi8a2i0UkDvdlmMaIQw2W73Eg7sUVNajAi46o4wqi3RwkZVxzC7GutdBVIWUXUdTbRZto7hxFV026YTTlDvehXhg+0RVGsb7Z5V5oJPJ0eClqlgFsfoN1xuRDR8iouZsAltVVgJNZHuJL3Wi8iozi1s3rvnB2AukyHmS9MSLWqmTnZ7h3pYJWEkWGtG+ZhboxNJohc3UYTKSKkMgK20aFoavbKJLTW2evvYDfrI7Wxjo4E8jGIImsM1pov3nEVeR2YRiRxHVYMMaJ5sIsUGWx2LxVbn6w82Q9B76m2vQ95PkF+DSb3KlYEEQrqkbhXZ8K/h/96/eL/D2uctjDEUQ4kNkqhsUA0Pkqi1uKYbmB2XcGqGlhxivLvCUjpBVzdQdyw6iYOUbC/xe8Y8SNhpInw2myJAjzGDovWiSrAVl1LQj5xTacTucLro6ZCvJHTKX9UhW54f8u38YU75b7Mez2AbdZr+FLHyHJX8MI6j0B9s8Er8RRLNA/TZmyjShbLFXNZHvKNxR2Q5VF9CSJfnT50FCebMPTeN7DRRBAXASYU5NX2TW5mDbOo6g60iY60Atn4QgBf1CFNhz9ZoN+TpK861tuli8ODOCEFlnpY/SCGaR+9GUYBN0cPytac5kT5BQAvw0uZLJBIJYrEY8/Pzb95ivssQQgwIIZ4SQkwLIW4LIf7m/Y7pz4KUkt4ei5eyLkFZI3trgyVjjGPvfex+h/bWRDPhzI/CTz4Df+1leP9PQSgDN38LvviP4Dd+EH7lu7yBI5/+EfjS/+olU9nD8PF/C39nBv7CL8DA/bPPS+XSICDrlqgKk0Q7x2JGRdsSBAObIASJZgMpdNSORbJSZiMaQkHBLWcwlQ4+X52O0mZGP8qUssKWJqhEBshW/KxbCr6kRdU1yWjz7HYnMFNeU6Ci2Dj1O1hIppoHMDp3cdUswWaN63GNXjeJVFRKq+OEVHj2XqNeNNjBLSlcCjex5SBHunUCfody2+FkZYhAc4sbE1MENRXbbVEMBUgVCpRiUUw3zW47xNmqw2rGh1taZlBPU6sJWkqbkBT0KlWi0kXgctscpuo3SFarCOmyt+tpUMLDVWqNCI4/+boJsqLoxGJncRvTxM043apn4/bca+mQN698XTPo24n9BPkbcOXi0zQDUa7Ghhm359F9o7RKF5g48533O7R93sIYPUHU+DBDa8uUYln8nTqNhkKgZqPFt2nIHLnyHI4iuDs4wuJejlwsit7dIdSp81LK0/xOiFVcxaYjwHfPeL/mdygGfRzbmqfc1ImLFfqabV5JKCi+YRyjiGUZpLQa+eYAmeQCG+EACNhNDxBo57HnB7EcnXhsh9vmHL7qMLlcm6HuBkv+HIWUVw24pVj0FMYZZIUrB48CElECKjrB3G1GbRUp4VrqHKdmb+MqKreMHo63O7gDMLBjobs+NswN+vzejaQl9mgHYvR2JCoOVneElnUZgBuagat08RFmnmG0pafRVZ0Hcg/wwsYLCCEYGxtjaWkJ236VCU77fCuwgb8rpTwEnAP+uhDi0H2O6ZvmzvO/yhEZ4nIsw3H3KtF8C5w4kVTmfof21iczBY/+HfhLvwv/cAX+3oInxfjRL8IPf85LoP/eIvwvs56/8ukfhnD2fkdNKuVVQXOOt1uVaWdZSDkoHUFE9aQD2UqRjj+J1moTrzfYTaRoOy1S9yqowVCRglJDY4hDYpVd1aXlzzG2qbDWUVA12DX8ZI27NO0eBkK7dAyDcDVPbvcqc9LlUOMAemeWduA8RmuOr/Qb9LgxALZL3s6z8EPJNRlRPbnYtvDie6h1iLjuVaJnCeKzlrkxfpBA3RsfUY1l0ByHRKmELR1AQDXI02NVkC6Dlp/tlg9VK5Dqhknru+waftKiwc3SQTLhOs2Qj1SpwOJaF39XZSDtuXFsdXRYecGzAnwNEvGHabWWeCx3hOntJ+k19W88dnrkUXBtWHv5m13Otwz7CfI34KlffIHtRIsNtY/Du4t8T/cAyfYiqi/y+i/e512L0FWM4UlS+TzFhPeU/tAdlUZdgmGhh/bIrnoXwasHT1HNB3igMUt/QWOwOsNKeoA9Nc3Z1m3ams68PMFw8A4oMVxF4qgKg40tlgsjNDO3OV0UXEko9Isx0uo1dCvCESFxWv3MdExinU0kCsvD3vZy5IaBoXUJBGpYdBEo5DK9DHTXmI0PkN2dpyNsqs0OkdIJjnCdpVwfLcNEUQS+GUkwc4fjba+T/bcC7+Hk9m3MbocXgo8RkBIydxldvYXOGBvRWfb0w5iaBbLFXvQA3bvrnOjOcV0Zw+rsEq6usxAdQYTLiFqSHdKMtG6yVWlxvvc86/V11qprjI+P0+12WV9fvz+L+w5HSrklpbxy7/81YAbou79RffP8wpefZ8E+Q1PxM5mfoxNI895Tufsd1tsPIbzBHr0nPG/b4Ye9BDqYvN+RfR1fHTIWx0vwot0Mq2lPGxtsrqBIQbxZoxTJonRrxBsN2r4Ac0qRkWIGW6qEwmXyosY4Jkm7yY7qglA5uK6zfq9Rb9fUyepzSFTCboBSIkGysEey1mAVm7FOFs2p4xg5HPcVliIKllAJOBplKRGOwRG/y6rh54S2iVBdIqV5HNFlrDlKUFxDKvCHhsvhcoN6IMheu0FQi1KKxpFAbmsbS22hKwqrjRjdkTxS1QmWarQdnaPtVQxpYJu73HJi9CpV1hs9GBmXdU2Q2dhhs+0joo6TDrm0fTbTJR26dc954jWIJ7wm17PRMHutXU4E4cVyHfdVdcgPgqK/rXXI+wnyN+Agba4NxgDI3C6wZ+4S+uQn7m9Q+7wt8B8/TqRaJZ8K4AqVU4thZi3PFjCQvEukmGaw1WJ68iiRQoNzpWsE2ykc5zoEdC4rRzlfvsZaOMV1jjGuXUXVBog0PBlF21RYWh2llZzmbNGloWu0/H2EnBUECifbPkDlwvZRDru3KfuSlJI6XS1AfHeLTtvzge0JONS1ChlthFRtF1dRSS7vsRwVRKsqojzFUfc6jqJx8fBxlBb4piWq2aAvvIYq4aoWI5puc/LubX6/99twgKhcZXJjh0LsOHWzxFPaKYYCZQDy4Qiy0+XDpWvcZJQzeZ1Id5aN3BBGdAej4z1UmELw/I27PNzn+Y2/uPkiIyMjKIqyL7N4ExBCDAMngbddG3o0o/FKVsGQHfqmV1jQRznzwfff77D2eQMxDINYIIJhGqiujdVOs/bVoX3FFnE3QMDpsJ3OIdwu2Xtjt6+ELPrtJOvuAP5omV2lwiEXdq0YQvNcJbKNUXbvNeqVggZZ/S4A69YhWgk/0WoVK9hD1a7hQ2Ok04vqFNC6syAEd30qvTJB3QCzPMqE6XAzohEUDkbCJrJVYjlURziH6XdeRMYMbrgWH9j1dMjT/YPEfClabo1ywCS3tUUl7iNpZFhpxPn2dp16Io2SX8JQfKSLdW/Ak2IRdC16pQUIlnpGKYQCZHd2QAi61gFQBdZYhTuFLBLxujKLUHASw0iRE0UA4s4KRcthut56lUUJQt/pt7UOeT9BfhU2F2cgFOJKYogRZxFNHaRZfZnx85+836Ht8zbAf3ICRQtgizK18CC5ksILGCiOJJ69giX7OdJe4/ZgP6Zj0buxQydykILrXXi/bB4haVcQfosN4afXuI2iD6C7ng45HwqgzEEjOs+poieJuJRQKfkiSFyE3UURNnfLE5yI3GY5lcbR29RCWeKlWarbI3RtjZ5IkedizxOrTjForOF32rSaKgs9JkFb5bIZYqpSwJRtnj19DgBj1rtkhHLTZKRCXUIjleWBW9fZiPawaAaYbNXImSn8Ha/4eFUXTIa9m82ev4kUgrN2DReFI6WD6Oocrqox76+jOD5MRWVeDJO/8UUGw4P0hfp4YfMFfD4fAwMD+wnyG4wQIoQ3AfVvSSmrr/L9nxBCXBJCXNrb23vzA3wNFq78Pic1HxcSCY7K68Q2ayATxLL7FeR3Opl0hm4wSMIqsd2J0DYUKnGBzAvibgB0la2vTt0rbaG4DrejKjEZZKU1TDS0Q0XUGRGSK3KECfUuTWxc4wDBtsFyV0HNdjBEhaCSZ6l7DJH07OC6oRDtlmfhebR5CL0zD1Li63S4FtMZcNNIVaW6doCIBk9FNaSEWKCDUxC8lGhiywHOdDqE/Bb1jsux0ijBxiqXp44QUj0/5GI4TKJUohEMYlgRqpaPA1WNmV4F2dhlXE1QaOg0tDoxR6NHKWMIiY7NLTmE5RdErQ663WVjIwRSkhisYnX8dP2Z102QhRAk4o/QqV2lJ5ijXnkBeB0/5M2r0PkGMoy3OPsJ8qvwqX/722zF26xoQxzOL/C91hTx+l30QOx+h7bP2wBzOIqaGGVoY5FifIh4rcQdxSBctTDTi1TdEUZrd2gaGnMDwyzs5EikehDdTYLdBk8nzwAwyQqucGgIk4Dfa+yoBWyKIR8nt+9QrIYIagsMN9q8mBIEjFGkbwtpBenX6tSbQ4jYFmXD2/7a6J9Ac7uo17JIVxCPb7GkrmE0c+QGFA50FrkZH6Fretq4OdkhXTzBIW5y9cAhz33TVVA2DAK5aQ7eq4p/OfZhHrhzDYCr5jiHOl1aI0XG1nbw2wm2/QskAwASmz1qkV6ilTYR2WDVGqFev4DidJnRU3T1Mmo7yQJDpHZeoG25PNT7EBe2L2C5FuPj42xvb1OrvT0vuG91hBA6XnL8KSnlb7/aMVLKn5NSnpFSnvnq1vZbhZ/7zO+x1jlHWY1wqDRN15/mo+dH73dY+7wJZPt7aJo6me4ey64fn5NkLa2jbimE9BKOYaBLGwkYzTapUpGlRAgdlU6pB0PpEAhWaKtNbupHOa4usK4LSrFRBvb8LHcU/HGbPRmk17hN0ZoglSzgCoGvUyNSuMgGLidqR+7pkB/G11y5p0P27AW38p5E0/YL8q6fMbUACPaYBuBc8xBJdQOAlzWTaGeVm2OTGFWvYltM9CGA7PYOXbcNQLkW4ulJ70E111TZbvlJiG0S3Shhc4tlPUROqXG7cJBstEYpaJDZ22Nxxybc9TOU8H7OclPA+sXXTWYTiUewrBLvzx7g1vbTjPnNb9yoN/IoSAdW35465P0E+VU4aHe5Oej9IvdM77JjbhH+/n15xT5/OrSUHzV3gMG1FfKpLIp0OXlXwa66iGADxd8gu+TpaF858gC1HT/nmwv0FzWGqjOsZ/vYUns4275NR9WYlScZCcwglCSuAFdR6G3vMl8cp5W9zbm84Gpco19MMCAvo9khTrsabjfD5UqK/tZdbGGyMjiAKxRisy6aaqNpFsa90aHZ+BC9rQ0K/hj9y/PUNJtOzSZUPMYJrlIMx1jN9iIsSeC2TSC5wGHLAgmfNY4zIdfoze/wZOwJVEAN3+HA0k1s4xAb0btcVx8j4W8CLvnIMJ25Vd7buMqLyiFCnTbR2jzLuXH80SJaI0kHk3GxxYvzezzU+xANq8GNvRuMj3ta6oWFhfu0uu9chDci7b8AM1LKn7nf8fxZiGdNns+pGLLD4O1Fls1RTnzg8fsd1j5vAtmeLAhBr1OgLgx6mn3MpRW0HYhEZgHIlUvYRgKt2SJVqbCZSmNLm8yO96AXjuTZFRUMRplilS3VpWumOLHgstRREQrs+Q36jNvYboghtUMlEiVe2iW3u8wdaXOoNYhmF7B9o7juy8wnNNpCEHQ0Sq5EODqH/S6rpp8T2gZCc0nszmEpbQZbYwTFS0hN8KThcqZgYekGa65D1EhTCwawFIWezU26ZoegZrLaiDGVKOH4IviLBWypcqy2gYJCVy+z0A3SK+oUuzG6PX42dI3M5g4l20dAP0IoKGlE29wuBrymupUXX/M8JxKe7O14SKfarXI4YPFypY7lvooOuf+BezrkZ7+1i/0msZ8g/wnWF2YQ4QCXUkP0O2tobj+tyssceOQH7ndo+7xNEEIQOH6aZKHATiaKRHB+Nsj8vYEhgdQsob0Ug80ON6dOEM17OuRQK0PHuQF+jUvKEc5XrrMcyXCNI4xp11D0AWJ1A6Sk6dNYXhimlZzmobyDpaqsRlM4wpsSNdHx3uvy1mnO6DfYjmRohVq0fCkSxQWqlR5cKRgItVnyz5HpTpJrbQJgbteZT2rkqho7nTGOdW8C8NypB1C6nt2bUB1S6TkCEhY0EzWr8cCta3yx7720hCDZ3eZATaUWOIatdvmiPsRUyKtybIW9z/Dh6l32iPPBzV5CzFNIZOmEdtC7MQRQEgluXXuZB3seRBMaz64/SzabJRgM7sss3hgeBn4IeJ8Q4tq9ryfud1B/WlbvPMNxJcBLiRQn3CvE1mo4MkYonrjfoe3zJpDNem4aPY6nCkq3+5nLdRFSEOl6FdpspUA51ovarpKo1+iYfqa1EhPlBDUZIhwts6NUOCK9gU7bmueYM7abYqWr4ErY9HuyN4Bta4pqMkqyUECYafJOnbA0GOr0ojgl1I533LxPo89Nejrk0gQTpsP1qIZfdTGTNsGNCnPhNo57hEH3MkpU5a5l8cROAsWxuTl6gKgvSscqkA/7yW3vUEhGiSk5VpsxPthosZeOIvNzxPUEasnGFjY6LlnRIOt4n+NucpRCyE9229Ng1xpDIATKeIXlYgapGt5UvdfANDOEgpPEHW/gStCap+G4XK81v/5gIwD9Z9+2OuT9BPlP8Bv/5rfYTLRZ0EY5kb/Dd1sHidtLqGb4foe2z9uI4LmTqEKjaTRoBHsYyBu8eE+HnMhewnaHOdraYHqwD8116FvZohY/QdHxdMh/aBwl6tTRAh12hU5On0HR+lEltA2XfNhP5m6Fmm+N46UGpuPwYkqj4c/hKl06lkNQrbNaG+NAeoaFZBypOOSTfYQam3TmRmh3DVLxbZ6PvkS4dIjeVIH+zhabWoKVHtCkwgVDYyCfosfd4MVjnvRDW/XGTodyNxl0VSwX1hPHeOD2ddqGn1kzwclmC9EXYGhHoLo6y8YuYyEvea8YJSzDz6Tj+SL7GuM43esA3NQVXKWLnyCzjOFb+AIhPcTp3GmeWnsKRVEYHx9nYWEB13Xvw8q+c5FSPi+lFFLKY1LKE/e+Pne/4/rT8p9+5VMs2A9SU0Mcyk9jBTJ8x3uP3O+w9nmTSCQSKEIhrjggJUanh4Uez21HLVQJuz4iVouNbD/CbZOtehMDLwXa9Mk4i9YYgWieXaXCCSm5a/US1laRUhJwDuBYKtuWoJNwiSib+JUyi91TWGnNGxgSTdJorQFwrHkYvTMLbgej2+FqTGdAZpCKQmV1iogGT8c0HClIBVs4FZWXIkUcmeNc20/UbNLtuqQaAwRai54OWTpIHIrROIF2CyFB7ah0XY14xccrg22w20y6YbaaPtp6mZQVoEcpYekKQTrcaI6j+xwMQyXYqrOyqqM4kkxfHWnrNPTE6+qQvXP9CI3aDSajI1SKXkL9DcdODz8CW9egXflzr/GbzX6C/Cc4KDtcGfb0Qn03dtk1N0n+8I/f56j2ebthjiVQE2P07C5TjI2QrFa4oZuEazZmZoG6HGakdpuWrnF3YIT5nV7SySxGZ4NQp8Yz2dMAHGERhMuOyBANWkigGrCp+E1O702zUezBiU5zutjhmbSkVzuI35xG68Y5qHTpNkdYES6Bzi5SKiyPTAAQuBbGVG1CoRIVUUFx/PT0ZxjtLDOdGCZcW8TBZbfdIl54kBPiCncHh2kZBggw7qiE+q5z/N7Y6d8IfZRTqzfRbIuX/A8wZNtU+uaZWJrGJ8dYi05T1CYxNBtkjXz8IM6dFQ5Zi1wVE3Tbd/G1iszGx3EDeUQtww5pjlo3ub1Z5fGBx1mqLLFcWWZ8fJxWq7Vv97bPHyOS8/F8D/hkk4GbSywYkxx9/D33O6x93iRUVSUVTUAgRMyqkG8nKIUFjbBAbgtSjh9paGykvUa9dHkbzba4FVNIyhAbjQEiZgFHa5JWXJ5Tj3BKvUNedajEJsiVAyx3VQLZLjXXT59xk93uQSKZMgCG1SBYusQWLidrRzDat+kE3ou/Oc8Xhgz63ARI2Cx4fsi6T7In/UzdG2vdsrwiwQONQ8RVb4fs9wOC/sYu8/3DyEIeBYViYgCAnu0tHDzt70Y9yvzkHhJBrGZR6voYsdYIOUE03wa31Cg9apW75TGSyRq7pkp2c4elAkSdBIPxDhLJ3Rqwe/t1x40nEo8gZZfH0/3c2n2Jw0HfN27UG3kUpPu21CHvJ8h/hJX5W3RDYS4kxhm35jD1UVqllxk7+bH7Hdo+bzOMvhBqeoKxpQXy6R40x+LAgoJTcRChOoq/RmbJa8Z48fh5mjsm763epK+oM1i5xk62h0VtlMfql6mYAW7IB5nyX0ZRc5iWCkIQdurc3DlMM3edh/IKWwETvzZGzr2BInUe6gRA6jy3eYzj7lWqviS7GR+W5iexUcC2Pdu4rN+ho7TI6OOkajvYikZmaZO1kCRSBLV0lGPyCo6iceXgEW/s9A0XPVBiLLSNIuEpo4dUos6xhVl+p/c7AIiwwMTWDoXIKWq+Il/SH2Qk4DWbbEcTuI0W31G8yFUxwfGCTrR9k5W+MczoFmb7nkeTYvDS1es8PuDpSJ9ee5qJiQkUReHOnTtv7qLu85Zl+vnf5Iga4UI8yyn3MrG9FgYm/tD+zt+7ib6BfprBIOnuLou2H9UNstxroq0qRMwStmkS6raQCPSWTaZQYD4ZQUNF3etBCEkkukteqVJSjnJGmWVVg2pkmMPLsNRR0AzJju6jz7iN5UYYN2qUo1GShS2Gtua5LW0OtwZRnDq2mcW1X2ItqlFQHBKOj4JwULshjvodlgM+Diu7qAGbxPYSLbVJtjNBgKeRpsJzisXDeYFUFJYCPmJmjq7mUDd1cptbNIKQMKKsNmM8oVToRFNo+TU0YTBR8pqtLaVDs6PT57ZpuT6KfRm2fQa5rW066KjKMXSfoJ5rcrsU9U7k62iGY7GzCGFw0O/SsltMmE0uVRu0nFfZ1es/C6rxttQh7yfIf4Tf+tefYSPTYlPt5djWPN/VGiXr20Voxv0ObZ+3GUJTMA8fJ7O3x2YugUTw/psh7rQ854dQ9ibhfIaJepOrR0+Typd5fOcVTHuAinsVDJWn1JOcrdxiNZLgNoOM6ZdR9REiTQ2JpBD2U5uOUE9e56G8pzF7JWVQMH1IXEzLQhEWt4tTnIzcZjGVxtU7VMNZEqU7VDbHPLu3aJFn4s+QrB5hQFvH77Tp1BVme01iXY0LZpSpYhFDdnj6zHkAzFvepSPSc42cq1CWknq2j/PXL3MjNcWG7uNIo0oikiHR8JLdK7rLoci9sdP+GlJReMCq46Bydm8Kzb2BrRvcMVsgFQKKyQzjtG/9Pr2hXg4mDvLU2lP4fD5GRkaYmZlBvppB/T7vOn7xi88y556hqQSY2p6m7u/nez+xP1r63UbvYB+WptDjFCjgJ9fqYzqno+1CLOzpkPuKeSxfCr3ZJFMus53KUpVtxrdTWGjEYntsKSXGiDLkFFnXHKRicGI5wMK93o7VYPBrOuSyNU4plSCVz6NqMfacJmFpMNjtQbV30Du3AJjxGwzJHC1DQdk5zITP5ZW4iqqAP2Gjb3S4FmvSdY4z6S5iRmCzZfPETi+61eLq5GEipu+eDjlAOr9HIZkgYCfZakU4U3dYyhq4pRWGjQy1mkZDbRKWCr1KhRieJd10cIhS0E+mkEdIl3ypB4DAWIWdYgqpB19XZqGqfmKxM/i7yyhCwde9Q8eVXKg0vv5g3f+21SHvJ8h/hENqhwvDGVRpk7xdYiM4R+7H/vb9Dmuftynhxx5EQ6Fp1qiGBxneVXlKMdAsl0Tvy3TkBCebC9zpzdLy+2HJoZU5TdueQUiXz4YfQMNhUN+irThoWgHNTCPwZBa74QAn12YptAQpd5X+Zptn0xA0DyDNbRwrwJDeoFYfoxvdoaZ6U6ZWBg+gOR30y2mkhERik0VtBbPRS25McLA9z7XEGLbhbf3NOW2yxTMc4yoXDh/HFSBsgbJmEOq9wbGOl/R/Pv5tPHLrIgCv+A9xut2hNL7DgaV1AnaOjfAsfn8YIVwcCpRiI4S3y6RliWnnAJ3GZTSryXR4GMvcRdSyrNHLVOMSs9s13jvwXq7tXaPYLjI1NUWpVGJ3d/e+rO0+bx2klPQMqHylTxCWFQavL7KoH+fAg+fud2j7vMn09vYC0Od4ete+1hB3s22EFIQ7dxASUvUK+eQgartIul7CVVVeClaZ6EZYsMcJxffYVEqcdCHfjWBpXiU22p2i2lUp2IJqUhBT1vErZea7Z7HSCprj0ExkaLVWADjROInRnsYlgK/d5MW0waDruWXsrY/hU+BS2KDlaPQbVdyuwtXQEpIw72uOkNALSEeyJuME2vNcmjpGuO3JGMqJXjTHJVyvg9VFIujUgjw3WgYkAx2DraYPTd0lZUVI67vsmQYJ0eBm+RCRQAsrEiBVLrC4ItEtQU+ujpAKRRH2EuTXKT4kEo/Qas5xOjHObv7L6ELwTPEb6ZAfhe0b0Cr/udb3zWY/Qb7HZ3/v96iGQlyKHuBQ9w5D/mN0V1+k/8Cj9zu0fd6m+A9lUVOTjK3Mkk+NE6+WmMMkWrIwsks0yDGyO42jCF46fIr1zSTHdZtoo85AdZXLvcepKSHOWTdxhOCOPMVweBlEgI7u0tU1xmur3ClM0uy5xsN7gisJnSEOMsAFNDvEg7aJtOO8VBxivHOTjhJiZagfR9GJ3+mgKS6qahP0tZFIemLD9NbXKPki9C3MU9ZtnIpDOH+SB3iZaiDM9PAESgeC1xx8yWWmRBMk/I7vMOPmOuNry3wm9Ql0QDenObR8h0bgONvhRZ7S30dvwOsy34n2Ya1v8YnyizynHGGg4hJtTLM4OEkgsoHRSgGCsGLxh1dmeXzgcVzp8szaM0xOTgIwMzNz39Z3n7cGX/ov/4DxzgBXIr08aL1MsCYZjUlUTb/foe3zJpPNZlGEQkp0vUa91iCLPd62v8g3SbghAk6bpb5hkDYDhRWQLq9EXXrcOAuNcSKBXVp6lWHF5mnlCMe0aYqKTSU2RW8pyFxbIZhrU3N9DBjX2OocJp72GpBNq0G08AobuJytHkXvzNEOPYLRvs2Xh3TC0o/uCrbrOkhI+Rw21CBn1FVAotduIXE53pggql5CAp/1ORysVNlOZWiUyphKgHIkhSMEua1tHKWJJhRW6jFSA0WkZhIoVem4Gscb66hSRRp5bjox+pUqy/U+/FmLDU0hs7HDRlMnIvrpjdo4istMRYHqOhQXX/NcJxOPAPBYMs3M3lXORHw8U/q6uUIew4/c0yG/9C1a6TeH/QT5Hpufu8XSgE1RSXJkdZHTnQg9D3q+ivvs82dB7wmi9h5hbGmB7WwPAslj1zXKNQm6jS+xTGKhTdhyeenUo/i2O7yvdIFsMYbZvogd83FRPcnj5YsshTNc5ART+gVUfYR43QQpaflUFhbGaKau8/iuQ1dVmYnHaWrek/xQxwUkl7ZPcz5wmdVEjq6/QS2YI5W/Q3lvEMtRGYxWuBm6Qa55lEFnFc21oWAxmzXoqanMMMTxxh1UafOHDz2GcMB3UyCEJJG7SVwK1oWCnYvz6NULPNn3EFVFZbRZoFdP47NHkULytB7ieNSzB9oIe6b9H2ht08LHB7YP4RO3afpDrPiqCMfAr2jMinGa1z/DwfhB+kP9fGH5C4TDYQYGBvZ1yPvw3EqLl/3j2EJnauk2ed8Qn/jBfd/6dyOappFJpBCBMEmryGYnRS0gKMdVxJpKHAc74KcQDQDgbzRIlQpMJ/2E8NHM51CEJBLZo6LUmFdOf02HXImOcmwB5joquinZMU0GzWs4MsiQ7lCKxkgWdhjYXuSWtDjc6keXEqkEkNYF6j6VFc2lx4lR1Gy0RpZjfofZsEFWa6HHbWIb22z7a5jWEVK8hIhoXHcsPrblA+DW4DBxf5quU6QU9NGzuUkpFSKhZ1hqJPhIp045kYC9OSJanESxhSMchHCIOl16HRuJwlJuhN2gj9zWNiCwnCOgC1rDNaZL92wRF596zXMdCk2h6wmG9Sa2tBnRytyut9ntWF9/cP9ZUE1Yeu5budxvOPsJMuA6DmPBDs8P9hOUdfx3OuxoFzjwvX/vfoe2z9sYoQiC5x4iWqmwlQ1gqz7Oz4a42NVASpI9r6B0Rjld2+P6gQMEO22OLdyhHj1N3r0JQvAHxkkyVhHCDntCJ2PMoOhD6A40fQ67kQBjM5uUjA2OVCvEul2ezCrgG8fR6rQtlaxeYbd2gHh2hc2QDgLW+8cwrDpcGsCyNZLJdV4JXCJYmqJ3uMXB9gI3oqMUIyUUFC6rNr07xzjMDV44dtqbqpdXoKwR7r/K4a6KK+H5xEd45MZFHEXjsm+YR1otipNFDi5sE7DTrIRmSAZ0BJKu2KMaGyS5XSEmayxZ47Srz6M4FjdCg1jGLkq9hyUGOdN8npntGk+MPsHLWy+Tb+WZmppie3ubfD5/v5d6n/uE47SZGNT4cr+PQblE//UNNtQpMsP70/PerfQN9tMMBci1t7hrhfDZSW4P+jHmBZHoIo6mMZTfwdHC6I0W2WKRlXSaLg5jm8n/oUNWSwyRY8zdYU1zkYrJ6UU/8/d0yCvBEAPGNQC2u0cpppOk9/aww33s2RX8qEw1J9CsVfSOp3++GfIxIntwVAVr8wT9huSpuCdRi4S7uDuC51JNunKC01abaKBNo+VwvDREsLnFy0dOEtXAdtsUojGitRotnx9f26Rq+cjVNK732shWkUk1wXbTR00vE3dM+pQSuuqgY3NDTtD0a0RbTQy7w9a259wVHa5Sq8RwfLE/xdhphUTiYZTWHXRFQ2165+LZV7N7030w8AAs7yfIbzv+2T/9N2xENa75pzhdu8H7/Q/i27pGINZ7v0Pb521O6NwRlEAKo71JMX6A/kKHrxgBQg2HUN9VGnKcQ/UblAImswMjLK5nSaSG0DrLRNpVvtjzMA4KD7q3QEiWxCjpcANQqAZsan6TU3szzOcnaKUv89iuw7MZlQlxlIz2Mno3xjkpcDs5XiznGG3cxBJBFseGcIVK7KbA1LroehfNrCOkSk96lP76GjvBBJn1uzRUm3a5S2zvIR7gZQqROAv9w6gWBC9LgrlbHHe9qXq/FDjPYXuB3vwOv5P8LiKuxAne4vDiHZr+k2xF5nla/xC5QBVw2YgP013d5LtKz/OMeoyeWoto/RZ3Ro/hi6xiNLJIBKYieOrCNT428jFc6fLF5S9y9OhRhBBcv379fi/zPveJ//hPfhCaJ1g2c5ytXUKqYT50cv+6/W6mb6AfW1UYsPdooTPUGObagERtCFLqNQAG8jsU44NozTLpWg3LMLnkK3O0E2LBGSeU2GNDKXLOcal0gzS0MgAB5xCtjsaO5emQ/UqFlLbIfOcsTg5U16UbCtOq38FG8mDtAczWNSztIIHGHl/uv2f3Bmxt5lAEbAdV9mw/k/oeSMEu1wCV99YPk1C8iaG/F9DINla5PjGFVi4iEORTQ4Bn9yZdT5u8Xosze9BzCkpUHfbaPvrcTcJ2kKhvnTt6mD6lyu3SJOl4jXLYR3Z3l/kNl0BXZyDTAASbnXuuE67zmufaGztd4L2ZCZb2vkxCV3n6NXXIN6FZ/DOv7ZvNfoIMjO82uDYWwBIGB26uookqvT/2l+53WPu8A/AdTKBlD3Ns5ibbuTH8nQaxDQW1YCGiZUSgTm5uCdWVPHnuA9gbCh8rX6a/YNBXeYV8LsN1/ShPlJ9j0x/jFfkQx80XULRBonUTAFdzuLFwhHrPBd63I2lpGkuxFELdQSCYanlazBc2HuRh/0XW4j20gm3qgTSp3btUi704rsJQpM5MYIa+9lH6rRUU6WJsN5nOGvSWVeadMU42byGky5fOP4pwwH9ZoKgOuZ6rxF3BglCRfRHed/FFfmfwQ9QUlcP1PXp8ma/JLL5sRL4ms9gMd5BC8JHWFjWCPLFxFJ97iWYgxJyvgZAqQcXPTXEQ58Z/ZyA8zMHEQT63+DnC4TCjo6PcuHFjf2jIu5RiJMdz2RCqtDlwe4ZFc5JHvuNtM/xvnzeAwcFBAPql16iXag1xp78NgLlXIOSaRKwWK33DCLfNQGkVgGdiFoMyyd36JNHADpZRYVh1+LJ6kjPaNQqKTSF9hMG9EPMdlVCuTdnxMWhepWyNMJDew1ZVotU9+rde4qZ0OFM7iOrs0QkdRem+wKUejTaSqG2wbbsIy8dBv82qL8AZbQ3FdIhtzdJVOgy0DuBXv4zUBU+pFu/Jg61pLGkmUTNDW4e6qdO7sUkzCDE9zFI9wePBAt1QAn1vBVUYHC95zdZtrUGhazIgm9TtII2+BFuGRnZ9m6qtExAHiYVd2qEOt0s+b7DH+sXXPNeJezrkB6NhZot3OBcxeaZUe3V3oeFHAPm6o6zfSrzrE+TttXl8EZ0XMhMMOiv4273US08x8cB33e/Q9nkHoEVN9AOn6N9YZ2UgjYvCxy9GuNH0ttVi/S8TLAxwolrj5ZNnSJfLPL74EkI5zC4XQVX4bf08Y611WhGNdRFgwHcFxZjAbwm6msNWPET2domSf5GT5QpB2+bLWRXbN4Kj1Wl1FdJaha3qBNHcCusRb9jHRt8Y/k4R98oIHVsjnV7jpeDLhIqHGRiuMt5e4WZkhEo4j4rCRdWif2eKQ9ziK2fOI5EoWwJR1IkMXuREV8OV8KX0d/Chi89iaQYvBSZ5T7NF4WCew3Mb+O00y+FbRIJBhJB0RZ5ybJjERoGcm+eqfQyr9iKa1eRGahLLXIVyD9tkOWdf4amZHZ4YeYIb+RssVZY4fvw4lUqF1dXV+7zS+7zZLN16ilP+GM+kMhxzr5FcqaKpUfzhyP0ObZ/7SDKZxG/6CRoGPqdFvdXHTgyaYQVWFdKuhhXysxf3fk8itSrpwi5XMkEiMkBzux8hJLH4JrtqmW1xmkeUWyzokmp4lIdvW0y3FDQdVn1BBoyrgEpMRtnJ5Mhtb5KpVFmQHYbsGHE7gmYX0NqXQVG47TcYk700DFB3j3PU73ApoaIr4E9ZmKtNbkXqWM4pxuQCvrBko2nxnRt96FaLS1PHiPtCdKw9diJBMru7FJIJIlaczVaE0zWXpR4/bmGBQT1Dq6LSUFsEpKBfVElJzxL0dnSUvXCA3FfHTtfHQBFwsMxsPocUKsy+9iBNn5kjGJygR/GaFHvEFntdm5lG++sP7j8DRhjmvvQtW+s3mnd9gvwb//w3Wcl1WFMHOL05w8e7o2SHHISq3e/Q9nmHEHvifWhCp60VKccmGN9y+QM9gL/lkBh4kYY8zJnqTTZiYRb6BtlYSGD0HkNpzxLoNvnd7HtwUHhA3EYKyTKDpMM2oFAKWVQCPs7v3GAhP0Y3fZlHd22ezKqMf1VmYcU4j4rb6ePFSoaR+g0sEWDuwDiu0EhcdjFVC8NoYwSqIFX6e4YZqc+zEUqTW5qmoTq0ShaJ3Ud4lKcpRBLcGD+IaguCFx2C2RmOyzZCwi8FznJIW2ZyZYFfzX0/ASnBd40TS0s0Ag+yFVngs8YTDAW9rbbVxADW5g4/mn+SF5QjnNkyibWuMjcyhRpexdfOoAAlJcWV5z/Px8c+jiY0/vvd/87BgwcxDINr167dzyXe5z7wc7/2m9wQZ6mpYU5vX6bqG+Cv/Nh+YePdjhCCocFBOpEYfe0tZjoJVBlgZjCAOa8Qi85j6zo9pQKOGkKrNejN77GSydJQXI5vRqnIKInkDmtKgUkZY8TZZUlzQWgc2uxjrq1iSViOB+kxZtFFk7ud89RyQUKNBo3sCLWOl3ieqZ/DaN8Ex0LvtnkmYzDiZgHYW50gpMJLUY2mozHsr+B2VC6GZ3GJ80RjnJSxDbbkih4i2lzg5SMnCLU8SUUxNYQiJdFqFaXTRCKo1cI8e6AMSIZbKptNH6qaJ9WNkNE3yfsMkqLB9coUvpCFYqpE6xUWlg00W5IbrGFbJnUjBbNfeN3znYg/jNO8Q1QP0K150/KeLLyKm4VmwsQHvaT7daQbbxXe1Qmy67ocNDs8OzaAITskb5XYMC9y8Md/+n6Hts87iMCJHrTccU7M3GArd4Bws0qnpBLY66IkdnF9NgPzc6iu5AsPf4Tumsq31W4xkNfpq14k35Plpn6Ej1aeZz2Y4EUe4bjvBRRtiEjTk1mgWdycP0y95wJPbLk0dI07yQxSLSAQTLYAJM+vP8RjoZdYTvbRCrWpRHrJbE9T2R7GsjWG4gWuhK7RVz/NuJzHcLt0SnCjR6OvqnFdTnCmNo0p23z2vR+6J7NQEIpLeuACWVdhQwrKfUN86OXn+GLvIxRUg7O1EqFcnJ5SBiEVXjSbnI57N5DNUBFbN3msWcFFYTx/ArX9NJZucjHoxxYt/E6SKxxhauO/Y3WDfGDoA3xm/jM4isORI0e4desWzWbzvq3xPm8uUjqMDPv4/JBGRm4z8socS+oReicm73do+7wFGBodpm3qDHfXKUg/w/UJrgwI1LIg6b/iHVPYppAaw2gUyJWLuKrKM8EKU06Im92jRBPrbCkFzrs20/YgIX0ZG4dO4DiRaoD5toLS18GVkmHzEivtMwSynv5WlTb+wgvs4PJY6TR6d4FO+BHM5g2+OGKgSw2/o7LR0JCuIBtwWFXDnFOWEIqLUbqBi8OJ+hQR7WmkAp81HE6WGhRiCUqVCj41SD0co6sq9G5sYOttTEVjsZ5gomcX1wgSKBZpOgZnGstoUsMyi9yyI/QrFVYavQRyDus+nd7VDZZrOlGnh8FYF0d1mS4rkJ+FwsJrnutE8lFct8PHesa5tP4Fjof9fG6v8uoHH/wYNPZg/dK3dL3fKN7VCfJP/9S/YiOhcSF4lLP1azxsnMW3fYlQvO9+h7bPOwgtE0AbP8PQyhJrAzkAvvulMNMNFQQkBl/Al+/heLXGSyfPkqpUePTuKzj6cfLOi0hd5dP6Q0y0VmlHVTaFn17fNVRjHH9X0DJsNmMhxq9tUvAtc6pUIt1p87t9Cqb/II5exuqa9OllditH0bLr7PhdkLA4OoVuN1Gf68dxFVKpdS4FLxEsHmLwgM2R5iwX0lPY2hICwRW3Te/Wo5zjBV44dpqWYaDmFdR1ndjYc5xre5eUX4n/AB+8+Ryq4/KHofM81GqzMn6Xk9O38MlJ5pIX2fadwqdaSFpspg4hby3wWOsaf6ieRa/OEGwsc238ART/DHp5gC4GOaXBbz19kU9OfpJat8YXlr7Agw8+iG3bXLly5X4u8z5vIv/xn/wgRvMEd/19PFx/Ac0N8vFHRhH7tpz7AENDXgPboOPtUmWaE9wc8h6gja0SIdck1mkwOzwOsstgYQXVtng6YTPgJlkqjmOqbQLRXQJaiy9qj/GweoMVTbKXOcLRZYPptkog4rCpBhj1vYItg4z6JeVIlMzuBsPr01yWFsfaffhcExAo1ou0TJW7usKIm6Wk22ilA5wOOFyL68RUCyNlE1kpMB+uIuyzDHIVPapwt93lL6zHEK7DhYOHSQbSdLrb7IUD9G5usZXLkBAZluoJPtxsspuOI3dnSWlpQoU2XWGhI0nKFn2OhURhJjfJViRI3/oGEoWOcwJFF7THKlzPZ7yTOfv51zzXifh5VDXE6aAg38pz0t/iaq3JVqf79QdPfBAUHe78/rdsrd9I3tUJ8lShwaUDESxhcOjaIpqoMPZ3/v79DmufdxhCCOJPfADDVaj6KpSi4xxZkfyWHiDYsEmMPENDHuZc5QqbsRC3RybYmEsQ6jmM1poh2irzWwMfoCt0HncvIYVkmin6olVApRKwqftNTuVnuLF1lGbvK3x0U/JKUmdQPU6f+gy6FeHDlom0Y3xu/ThnWs9TN5IsjaaxVD+p23VUAYrikg416IouQ+EjDFYXqRsBMvOLbAQcgrsuxvajPOo+TUc3efrMeZQ2hJ5z8cXWORxcR5Pw+4EBelI1Hr5xif88/INoQLI7x0RN0jHO0DJq/LrvOMdjmwAsJ3SwHX44f4kVkeP7lsaJ2M9TSGRYDpdRbB8Bxc8lcRz9yn/jQPQY47Fxfu3Or5HJZBgeHubChQs4zttj626fPx/FYJov94bRZZepa7eYM6c4/7GP3u+w9nmLkMvlMHSDiKETtmqUW/1sJwTluIZ+RyWjdGjGIrRMrxfEaHXo39niei5OAJP4WgZXChKJTdbVAlF5gAeZZVF3sfQE77kpmG55r50PhRk0rqBgsdE5ST6XIrO7ixUfYqebx0DhTOM0RmcatbOM4ji8lPQz6vaAEFRWTpDU4UsJlY6r0husY1c1nkuuYctePthKkzJLOF2XtpUjWl/g6dPniLodXGmTT/ZidruYVhet7dJxNdxKiBdGa2C3mXIjrNYDdPQ8GStEr7pLV1cIizYX2oewAxC22gTbDZZWIghXkhwrU6tH6JqJ19UhK4pJOvV+zPY0pqIh6l4T3udfrYrsi8LIY16C/DqT+t4KvGsT5BvXXsSOmzyTOsykNUvanqC9+xSDU++536Ht8w4keH4QrecEZ29eYG3gCKFWjcCajrZrIaIl1GiBgZl5TEfye49/O76VDn8h/zKDeT/ZytOUsile0M7ynYWvcDfSw4uc4Yz/Kyj6KImaD5BUAzrzN8ao9bzEt224OIrCV3IBmqaGxCXacdBEhyu7pzibvcRMthdHt9hLD5MszlC+e4BWV2cgvcbn4l8mkz/PeGSRhFVm3U0w22cT62o85UtwaNci527yO+/9MAC+ywqyqxAff5ZJS6XuuNzpeQ9PvPA0t2MHWNATfLTeIH+0w5nbBUwnymz4Bn1RBZDUtQLl6AADWyVissp89zhW9SvoVp3LfcewjLuoxQH2SHKWaT798jzff/D7mSnOcGX3CufOnaNare4PDnkXcOlLv8BRf4bnkr2cdV4hsdWgPxFHN333O7R93iIoisLY6CitWIL+9jrT7SSmHeHCRBTjriCduIGrqkxur9EO9OCrVOjL5ynE4sz42jxS83HHnSKe3mBZ3eU9jsDuquR1T1vr5xStpsG2Jaj0gCbaDJjXmW8/hNrfQZESDA1ZvkAJl/eWzqG3b9EOvodAY5rfGTeJySCGI1gr+kEKwkHJGiHOa8sgJJQvIpGcqx0hoj6LBH41YHO6VGIj00OlXMVU/JQSWSxFYXB1Fak0MBSFuVqayPg2UjOJ7BWpWSanWwsYroHi3+SaiDGklJirjhLt7bIZMOhd22B+TyNqxRjLtnCFy0xV91wnKhuveb4zmY9g2xW+recAV9c/y3jA/MYyi0Pf7k3p23zr7/i9axPkl/7TM9wZkRSUFGfn7/CAFWHoIyfud1j7vEPR0wH0Y48wtLLC/HAGWzH4Cy9Gea6lg5SkRr6CXp3gkfIuLx47TtBqc+zGNO3QQ+w5z4MQ/FLocVJWmXiwTEMRaMYGum8Yw4FywGYzHuL8nRusdev02dscqdT47T4YNE6i+u+itOOc1Nq06geZVV181hpS6sxMHUGRLuGn4hiaTSRSoGhuYLQyDB5IcLg2w9X0BLHCbWxc1hotejaf4H3iD5kbGGE514tiCfyXFaIDF3jQ9qq4/yHycR7JXyZdLvDp5Lcz2bXYitzg8NIclnGW9dgsvxv4dgaDZQCWU33Ymzv85O6XeFI7xeNbPuKdC8yPTNH1z2O0U/gUlVviEFvP/xIfHnqCiBHhUzOf4sCBA8TjcV566e01ynSfb57PPvcKL/gP0xE+Ti5eYcsY5Qf/2o/d77D2eYsxMXmArqExam9Sx2CyfoiLw00USxBv30KVgp5KgZW+gyjdIsN5zwnns4kmE26GG5UThP1FRHCXfq3N76kP8bB+gS3VZqvnLMeWg1xrqkSyXXYJMGq+TMdNcDBapxoKk9te5cDKRS5Km1ONEUxXBUVF6TxJOagyq8Oom6Og22iFg5wP2tyKm/RoDXxpi+j8DmuBMpr1IH3KC2gRhZvtLj+0mvJkFhNTpIJZz80iGqB/bZ3tXIq0yDBfS/KxToPdXBq5fYukliKx18ISNqqwiTtthpwuLgp3+w+wEQ7Sv7qOjYpjn0Y3Be2JMhd3coCEW59+zXOdSDyGqgZ4MKyxUd/ggZDFS5U6e91Xmap36Du9qXrXfu1bv+jfYt6VCXK9XKQnYvPk4AGS7h7+VY3d+pc48vH/+X6Hts87mMR3fQjVjKB2NtjNHGd4u87n9ACJYpfw0AWqHODU3ivUTZ1njz/I5mKC0WiWcHOHwfIyXx55lLIS5aPdF2gJjVfkw0zF5kCYdA3o6Bqj9XVe2jxHre8lntjQWA77sHwjpMRlFKnznpYBUueLK4/wPuVJNiP95DMK9UCG7NISrXoM1xUMx0usGZsMuScYa80BYK5VmEkKevKCzeZxHmpeQJU2v/veDyEsCD0Pit5lpPcyEUdwQ9Ow+zJ85MVn+MXh78RGcLZeQhmMMbEWQkiFC0aZE/FdADaDJSwzwHtrZSw0hnYP41S/gKuoXI7309VW0GoDLDLE+61n+f1reb77wHfz5OqTbDe3OXfuHOvr66yvr9/PZd7nDaRR2eV4b5TfG4gzKacZvrZKWc8SSiTvd2j7vMUYHx8HYFBWUaSDUZtiZrCLo4G6AFlXR/p1ZoeHAYhXCvTsrPNCT5CEDCFX+nClIJ1eZVXdpcsZ3ieucUeXtP29fPiSy9WmhhAwE40y6nsFBYvVzkPs9mXI7O7iJgbZsgr4UXmgcQ6jfQO1vYJq2zyZ9jPp9iOFoLB4irQOn0urtB2VgVAFp6byVPwuthzi25oZ0v48TttlW6aI1xd46vR5YlYbR1rspocwLAt/p43esOm6Gk45zFOTdbDbHLYCrNYDdPU9sp0o/doGbV0lLNq83DpKNyKIteoE2w0WlpIoriQ9WabSiNAy03DjN1/zXKuqj1Tyffg7M5hCxdd4EUfC7+6Wv/5gfwymvg1u/newO9/aRf8W865MkP/LP/pZ5vtd5vRxHtm+wnc6U/QejqJoxv0ObZ93MMGTPWgDD/LIpRdZGTqA7nQ5e82kVnDB7BLIzZKeLpLqOHzxPR8jtVHikxtP0lPM4Ha+jBX283n9UT5UfIm78Ry3xDDHfE+h6hMkKzoSl91IkO4Vg1LqAh/ZstFdh8/2aTQDfThqC7srSGo11srHSfXNsxT3gYCVwXGCrV06L03QsjWy2UW+Enma+N4ZBkZ2OdBc4lJ8klIsjyEVnvbBwMYJTnOBP3zwEbqairohEHmd2PCLnOqo2K7ki+nv54mLT1E041wMHOJjjQa3JpY4ffsWppzkbvICi+Hz+LUuCJu11CG4PcsHapf5Pf0cydom4dYsNw6eQTVuYdZ70ARsKX1c/Mpv8z0Tn0Qg+PU7v86JEycwTXO/ivwO5qf/+T9iWjlLUYvx8NaLNPQ+/ubf+OH7HdY+b0EikQiZVAY1HKe/tc50qw9bM7gxHsF/TSGZuEPX7+fA5hKWmcKsVhnc2WUzlWLF6PKBosGMe4hEdo0ldYcPODrCgnWjAUCAMzTqJhtdQbkPDNFg2LzI3fZ7viazEKqCUniOPC4fKjyM0ZmlFXkv/sY1PnPAwJA6QUdjpaYhHZV0yGVJjfCYvoBQXZTiJSQOD1VPENe+jBTwq6bNg4UqW+kspXIFUwlQiaboqiqDK6s4WgtT0ZitphkZWsc1g4R396hZJucadzGkjuvb5ZqMM6IUmasOE+pzWAv5GFhaZa5oELOyjKbb2KrDjZIGO7dgZ/o1z3eu5xM4doXv6B3lytpnOBLy8+nt0qsffOIHoF1+XX3z/eZdlyC7jsNYUPL5iXFCskbqeo119QVO/Mg/vd+h7fMORw3qmA++l2SpxGJfkLYZ54PXA/yB7UO1XdJDTyHtw7y3tMzVsWFafj/x63kqPR+g1b2I6tj8YuID+GSXw+YSrpDsqX78wRSqhN1ol+1YkA8sX2KmGkH3L/P4bpXP9apMipNEzFfQujHeJ1XcTg9PFkY4UnuJtpJg9uAQjmKQfsXBpzroehd/sAiOyUDvEGO1OXYDcZJLd6hpDla+S2z7Qzwuv0zDF+S5kw+gWoLQiy6BzBwn9DJCwq+FxxkJ5Dk5e4tf7vkESceTdgQMP6HmATp6k8/oo5yIeZP1luISCfxQ8SYr5PjxpXGM1tNUIwnmNAVLzeNr93CTg3yw9QUuzEneN/g+Pj33aRzF4fTp00xPT1Mul+/rWu/zrcexW4yNRPnscIheucbESzMsaIfIDI3c79D2eYsydXiKeijIRHuZHSfEWG2Kr0xJ1Iog515CSBjfXWel/zBqu8BI3tPa/mayxpSb41r5JCFfCS28Q7/W4jPiMR7TX2RTtdnsPc+p+QBXmhqRtMWW4ueg/2ksN8RwSKMcjtK7ucLY2nVekV1OtgYIOQEU2UXtfIWmqXLL1Jl0+6noLur2KR4IOryYMogpFv60hX+xwmykANZDjIlLmFGYa3b54eUsqmPx/LFTpIMpOtY2W7Eg/evrbPekSbkpFupJPtJosdGTRO7eoVfL4N/r0lLa+CVkZY1Bp4tE4WbvITaiIQZXVnFRaHVOo+qC7qESl7b7vKEhN1+7ipyIP4JhpHkgaLNR3+CRUJtrtSbzzVcZGjL6OET64covvxHL/i3jXZcg/8zf+scs9sBN8zCP5i/y/7R33+FxXPe9/99nZrZ3YBe9gyBAEgR7ryIpkpLVJdtyXJPYiRMnceIUO/U6N797r1OcOI4TJ7Jix3KXJat3iqTYewUJEr33Rdle5/z+AOTQNkVFFkmQ1LyeBw93ZxfcD75n9uzZKWfuZSkBRxDNYp/paIb3gNy716B4SikYaaa/cBH5YxMcl1ZyRlNYi5qIKqXM7TtEVhE8v2Yr4Q4bq0WE/IkE1WOnOVU+n06tjLujuxnVHOyX61jkOg3CiSo1dEXBlQ2xr2MF4cKDvK/PQsSkcTGngLSpF4GgJg6KSHOofxXrcg9yMa+ItFVnNLecwPBFxnvKSWQ0ygJ9HHOcpiy8lGqlDWcmynjUSmOBQklIYY89wNyhMH59mKc3bgMJtsMKUkJBxQHKMgqDepa+whXcsX83zxVtJKJYuDsSpXtBjGXnBrBlcmnxHCfPYwYkSXWC0dzZFLT3kJuZ4EC2ARE+iJqJcK5mESgnMYdKkCiYVROPv36IX6n7COFUmOfbn2f58uUAHD9+fGYb2nDV/fVf/DqR9Ap6zPmsH9tLRuTz6Y9tm+lYhhvYvHnzQEA1Ywip4wnXc6oqRsYElgsZ8qVG1mGhpbwUgJyJYYoHe9lZ6iFHurC0F5OSJvLz2+lUhxEsYTvHaDTrJK35bD1p5uT0VVHPeXyUWU5gFmHaEhsYKg2QNzJCIn8Ww4k+NATrw7dhiR2F1DimdJIXiqzU6EUADHbNw6nCvhyFiYyFOscI2YTKYdcJsuRxX7SKfEsvMqVzxOImN9LGziWr8MYi6DLDUMFsVF3HHQ5jiUbJSoWxkI/9c0ZBz1AXN9MZcaKY+slLeSgy9TE2fdGQg+GF4JZYZRpvZIILbW7UrKSoZoJE0kbIlAuNP7nizBOKolFQcB+mxEW8mooM7UaBy29FVlRY9GFo2wkTN+5VUN9TA2Q9m2WeSeG1ugqsMk7RiRGGtCMs/tw/zXQ0w3uEdU4uWtkKVpw4QkdFBQLJ3Qcd9IUALYuz4Cyudo2acJLdqzeRHxzngZbXcCZmE9R3gkXjCctGVoQaGfK46RMeyq3HUM215IY00mqWAZ+LyrP9DDobWR5M40/GeKFQwWKvIWMeI56yMtsSJhSex4g3AtkhkCaaa2ej6imsuwOAjtc3QJPzJI6xenLmJZk/2cTR/DqQrQgEZ7MJivrvZKN4ncaqWgZzclGiAlOLCU/5QRakVKSEJ133c3vHAczJFC95NrApFuO8q538sRGkspAhVyc/sd1BuWOqI+3IzUefnOQ3R3byuraI3x5y4U4do7lyLvFEP1nSuKWbU8xl+eRLjAeLqPHV8JOWn+D1eqmpqeHEiRPGlG+3EF3PUFSVzxNVTnwySP2B01wwL6R64aKZjma4geXl5eHPycXk9FAS7+N8tJK0ycyJ2T6sJxXyc8+Rstmo7esgZc3HNjFO5cAAIz4fZx1Jbg9ZOJ5Zhj+/ky6tn61ZQSRtZdw0ShYdaV2LOm6nPakQL8sAOnW2N+hJLsZePnV8rS0Vwzm0gw6y3B5cgZYZIOVcjTl2kJ3VVmIyiz9tpyuhQ9JGtVOnxeJirdaJYsliGThHVqRpCDfg1l5EqoKfaGk2DyUY93gZTKSwqS5iDgdRs4nyzi5S1gx21cKFyQCr8vvJ2L3Yh/tJZi1smGhGQUE3j3M+5aVaGac3VogoMdNtt1Da1k132IxHr6I8J0XakuFM0AQTXdB/8or1Lix4ACkzPFhQwv7u51jvc/Lk0Dj65QbWCz889e/J713lVr963lMD5C//7l/RXgTHbPNZM3GMO+RSck09WB2+mY5meI9QzCq2DZtxRuP0B3QmXRWsvKjwFDa0tE5e+eukZQMbJs7TlpdDe2EJ2UadeOlGlEQjjmSUH+Tfjo5grXoaBLSLQjwuOwIY8iYZddpYM3CaI2OzSPma2DqY5EDAxGx9IV51D1rGwfaUE3QLL3et4Lb0K4zaiugvchKz5lDQNIrImhECAp4x0lJS6aylKtZKRtGwdo8wZNPxDWZJRBexKjV1zO9rK9ahpMB5UMfsDFLn6kCTsNNlRi30sOXIfr5Zdh8mCauiIaKVbmq6rQipcMo8ySLf1GEWo9YRUjYXq6MhUpgxD5XC5Gvoqsb5kjmkxCkYLyeKgxWmDh4/2s2DNQ9yLniOC2MXWLp0KdFo1Jjy7Rby11/4KInkSlpsxWyZfA2RcvOZj22d6ViGm0B9w3yiLidz4q0MZV3MCs9j15w0akSQlziBIgVVI31crF6IkpqgergdJZvhh4E4ddlCzgwtwKwlcPu78ZiiPKtt4Q7TXlpNOgOFy9h4WnA8puL0ZulRndTZdiHRyNN8DOcGKO3poCQ4wHE9SV3KTyAdQM0OY4q/QUYVnLA7mCcrSGiSbM9aFtmy7ParmBSJK5BC6UxxwjdEJrOK+bTicGfoD6d4qLcQUybBG4uX43d4iCf76fd5yB8aYjgvD1/STWfUx4pImvZiN/poKxVaPukxjUkthEtXKRUTFOopBJKTgXn0eZ2Ud3UBMBldiFAF2foxTg0XIxUNzv3kirV2Omfjcs1nnjnEUGyIZfYIPYkURyajv/hkXzlU3wYnv3vDXnr6PTNA1rM6dVaV5+fNwkKSyiO9BLUjLPnC12Y6muE9xrelATV/HrPbz9FXXI87GmJw3IxnNIWpsJWk6qGy7RSqLnlq032ITp07Y+epGDZTOLmfvqISjlsWcF9oJz0mLwdZyRLHUYSSgyNpAyGQqs6x1npCBYfY3m8moygcDfgYc0SR6FjjaexqmPPBRVRVdNCR4wQF+ouqcId7iZ6uJJw0U5jXzW73XoqDyynK7acs1k+n6udioU5eQuVVj5mivlLq5DleWrsRCZjPKpBWyKs8QE1aYSKtc9F/B3cc2s1Jz1x6tQD3R6JcrOpnfvNF7NlZtOYcY8C5CKuWBlL05M5FPXeOpZGLvGBexvxoN9Z0N2fmLMKid6FlXNgVQTsVpFteZ3lgC2bFzJPNTzJr1iw8Ho9xmMUtQsos+VWFPD7LRa4coWHPSc5ZFlO1YOFMRzPcBObOnQtCUCXGpi4BHWrgVFWchE3BdlqSr+gkvS4Gcn2AwBUKUdXbyYHSHOzCRnW7i6DMJb+gnXZ1CHd2Hls4SaM5i646WNpeyumIRlZCY44Hv9aOR+vlQmIzIyU5eEIhogVVjMamLtm8eXILlvhRstKCORnhqXIrZVk/ig49/aVYVTiXozKctrPA1o/MKpw1HUXHw33hOeSbmhEZyVNOK4WhdvYsWoEzMolEZ6RoLgLwjwWxRyeQCLrCfhrn9AOS6oigM+LEpXXjyzgpMvfRaXNSqIQ4NLEAszsDVpW8sWHONVswpQWlVZOkUhYmFC+ce/ptL/BRWPggSrqPcotCbPw17KrCk0NvcbLe4o9BqBfadl3FFr963jMD5C//7l/RWq5w0jqfjaOH2S6Xke+ZwGLzzHQ0w3uMtcaLVrGCBY1n6CgvQBcKDx300BIWoErcxUfRBgMsH49ycNES7IkEd5zaTcq8nNHsflAVvm/dSHliANxZQoqZgPUcqnk23oggZkkz4HOy7sJpOk1d1IaTVERDvFCokGeei7T2k0q6WGRKk4pVcCpjpSR8Bl06aZozC10oePZZsZpS2O0hhh0t2ELVuGpN1IaaafWWYgo3oyPpjSQoHtjOOnYzkJNPU0U1alJgPS1wlxxnbmbqb37SuZyF6RbKh/p4PLCd+ckUEfrRNIElOYu4OcKT5gUs9k6dJNPtA6TkE5ONnGQ2v9XlwxrZy4i/hH5UElo7SriEDsq4RznAq2fD3F5xOy+0v0BST7J48WLa29sJBoMz19CGq+J//clHiWWX024tYsv4DkTGx+997M6ZjmW4SeTl5eHP9aO6cqiMdnImWgHCyu75eVjPKBTkHCdlsbCk7TxhTyXWiRHKBweJ2B284Y6yLu3gYGw1Xl8fw9YebteztGaLsJg6iZNhwr+e/AEnFxMKsiJFWirMtb1OMD0Lf0kaXQg8oVHy+ndwRma4fWwRSjZKxlaHKb6Lk6Um+pQEFVk/fXoawnnUOzJctDtYovajOTM4e1pIKUlmRRfgsrwAJsGrpHjfIETsDnqkCbvJQ9oE43Yr5Z1dRD1mXKqNi6EAd3gHSbkDmAc70aWN20bbkEh0LURX3EGVmGQ85SVenkOHbeowi5GECZeYR7E3Tdqe4nTQApM90HvsivUuyL8LIUzcmxdgV9dLbM918+zwBIms/otPrr0T7Llw4tvXpvHfpffEADmTjDPbrvJs3RxcMkTRiTFG5T6W/cFXZjqa4T1IqArOrZuwZgXjjhjBnDnUd6V4UtixJLLkVbxOUtSzeuwkQYeVQ3MXM3nRhqtwHq5IO7mxIM8VbSSmWNnCUaSERmrJc+sIIOhOM2m3snj0ArtHFhPNO8n2AcmpHDNlciEmZS+qbmFT3Ako7Ohez1rbHno9xcRckklPKXnd3STDbrK6oDAnyKSIUKPUU5rsQJE66kCILregfDBLm1LJ4skmTDLFK6s2ILJgPyRQLXFq/Wex6HDEphMqms3Wg3v5VsX96AjuiUQZnKeyuGkCS8ZBq/0i1Z4oIIkro0z4yqnp7ULVMxxJ1mGO7EHINI11ixH6OczRIhQkdhVeOXKG+6sfIJwOs6NrB4sXL0YIYWxFvsmlUzGqqov40SwvATlEw57jNJnnU7FgwUxHM9xE5k8fZlGXaCOk26kJNbB7bgiREQRGW1CloCQ0ypnaBYhsjKrRDizJOE/mZ6jJFtLeU4ciJP78NjRzmFfEJu7T9tFokYz75nLHsQzHYxp2u067xc1syxuAjoUyevOLKevuIi+V4pQeoyjrpCJVgynVhil+ACkER1wu5upl6ApEOldTb9V5xa8iAK8/gezX2ZfbSzK7ghWZEbzOBJOTKVYPF2FJRdm7cDl+h51oso+h3Fx8ExOM+3x4oxZ6Y26qonChxIKc7KFGyWNi3EXQEsSXtVCpjpEj0qjoHHXNY8DrpKSvF0XqjEzWgyKQDUHODJcgFdPbXjTEZPLh92+mUhkhGB9mgWWUyUyW18dCv/hkzQINH4SLL0Fs7Jq0/bvxnhgg/8dn/5bGWRpN5lo2DRzmLr2esnofqsk209EM71GetbMwFS1hQdMpekvqsCVjaL0mbKNplLw+dAvkNnfgTEte2HgXtr4EDwztoXzEhyO6i0jAy07Lau6c2EuHJZdjYgFLHAcRaj7eiB2kJG5W6b5QxET+Abb3T51pvSffyZhbQRcZEsksAVOQ7on5uMuHGbZlQAq6yiqwpMJkD5YTyWjkBTp53bub/JEV5FSOUBdq47y9jM68OK6Myi6nINC/lKUc4fXlq0mrCqZWAWGNvKqDzE2rxFKSw+772XbqDUY1H8ds87gvEuFcoJPi4V5UOYdu7zlest1LmXMCgK6cEvSBfj4YPMiz6mo+N57BlTxL4+wGspEBsmoUl+7iDHNYGXqVaKicMlcZTzQ/gcvloq6ujlOnTpHJZGawpQ3vxv/+s8/Qpq6gx1zAHcMvk8wW8ed/+ImZjmW4ycyfPx+AchHBkk1AeB7tBUmCuVbsxyHfHGM8L4AiM0hhwh6KMLurnZMleeiKibUDOs16LXkFHbSqAxRna1itn+OcOQNCpWxyMc0hEykdmgJOnNo4ReazXIjfxliZE3s8TjyngLFoExkk28dvw5w4S0YrwRoP8nSVBZ/uwJpV6A7mYFJgwKfQn3Gy3NQNUtCpH0Fi457QQgKm4wgdvu8UlIW62b9gCfbxqQHmaP5cJJA3PIIzOgYIWkN+hmp7AEFZKEtX1EGJbMeuWygy99GoeSlVxjk+UY/dnSLptFA4NEBjs8CaVqmoCJHOmBnFDeeeettjhgsLH0DoERY6NAaHXybPrF15TmQ9DWevPPCeCbf8ALm99RyeHJUf1ywlTx8k/1yC/tjzLPrIX850NMN7mLnMhVKzgrqWZrrKcsioFh485OF0VAUBuWV7IFzJxtExTtTVkNE0Vhw7wWjgdsLpQyAE37FvwpONUOAcJSkEFks3mqUGVxxCjjR9OU62tR3iXCZKQSbEgokJXihSmK3OR1ja0JNuVqkaeirArvFSGsJ7SCp+WmcVkVZt5B6ROLU0ZnOStLMHc6yA3HIf1ZFWRuw+nINNpIVOZDRB/tAW1upvELU6ONSwGDUlcBzRceafY6GMA/AjTzElnjBLm87yzZKpOZHnxcdI5XsoHgmgKzp7NCsrc3oA6HdOkDWZuTc+QB8BXL3FiNAOUhYnbYWzSOknYaKCGHZWmdr59v5OHqh5gBPDJ+iY7GDp0qXEYjGamppmsqkNv6TBrvPMqajkR1X5zNIvMm/PaTpsleQUFc90NMNNJicnh8KCIqQ3QHWsnbPRSsy6k5cX5mFpVShyHiNtNrG8tZGRvFrMoWHKRwZJm8w85wuxKJvDoYmVOOwTxDxt3Eaag3IuNVojo0qG/qK1zG2z0xhXsZQliesqc207iel+yvIlKc1E3kg/NT27OCQzbJiYiyp1dC0HNbGT1nwzbUqa2dkigiKNPlrNIkeaRqedOVoQky+Nq6uTqBajML4Ip/VVhEVwIJvkvn6NuNVGl8mNy5xDVkQZddkp7+piwu/Grdi5GApwr32EuC8fbaAVDQerhwdIizS6GiectFBNiFjWxkhFGR12K2XtXYTSGlZlCXnuLClvgpNBB0SGoHPvFeudm7MekymXbTkuXu9+lXsCHnYEQ4ynL7OxomD+1M+pG282i1t+gLzvH3/EwQYXg0oh288fYkO2mGWf/nWEcsv/6YYbmBAC97Z1mE1uEmKM4UAD1f1RnhZ2nOEMOVW7SIjZLB05TlJTeXbV7Yy1Oal2OygKDlMc6mRf6VIGtQDbsgdJS8ExuZRKzwSgErVKYhYzs0NdvNa/mlDRfrb2m2l3mfAoDaTNJ1CkxrKIBSHS7O1dy9L8M3Tm5JM164zmluEfaifWU0Aqo1IS6KPV0kl9bDVlSifOdIzIuOCCH2qHJQdcOcwZnsAnx/jx5qnjQ+37VYSapaZ6F2VphTap01W8nod2vsCzhbcxpHn51ckQHXPGWNzUjiNdzAXfYUK2KhzmJJIEff45uM+epCHaxrfVLSwaP4spO8bRBSswpbvQsi7sQtBFKam2N1jgvR1NaHyv6XtUVlbi8/k4duzKx8wZbkyPfvtf2JlbR0hxs63lZQa0Wv7mi38807EMN6kFCxuIOWzMSXaQkBZmhRrYVzt1mXt/Tw8mKfCm4pyqrQeZpmy0E3d4gucKVar1fCLtBaSkmfz8NuKmCfaxkfvVfZwx6yRsJWw9qXE8pmIxS5psPioth1FEkmRmDl1FZZT29GCzuTmXDeOVZuoTKzAnzmGKHQXgoNdJnSwFAePdy6i1Sp4PqGR0QcAbQx9R2OlvJ6EvZnNKx28PkZhMUzlZgDUZ4Y1FK8i1a0RTQwz7C3BGo4RdbrxhwWDCjSeucb5EIKNDzFPz6Z/wELQOk5OxUqWOYtV0rKQ5aK5nyO2gcGgQUzZN/3ANCIHaMMb54WJ01TJ1megrUBQThQX3kc8QyfQYs5Vu0lLy7OUuPQ2w8CMwcAqGzl3FFn/3bulR4l//yReJFQleyFvB/OQ5aoeKiYw/T3n9xpmOZjDgXVOOqXQla48epLtsFqZsirpGG/poBjwhLDnd2JrHKYlleWP1FpzBOB+98CzeSBXp1E6yHhvPWdazYfIY7R4/jaKKpY5XUMyzyRu3IoXOsMdO3ukww4G9bB3MYM1m+HGZFZu9kKwWZTyhUW0KEQzNZdgXJSN7QTdxft48FJnB9pKflBTk5vZyyLcT7/Ay/AtSLBk/zXH/bOI0o6FwPB2ntO8utvM8Z6vncLGsEnVMYG5Uya3ezbL01MnP33DfxcbwCcoH+vj3woepT6bIKG1YzSq2VD0h2yiPmNexwje1FbklV0NmM/zByGHOUM0H20qxh19iIL+KLoePhNKEEiqhk1I+oe3kBwfHuXfWvfyk5ScMxYZYunQpXV1d9Pb2zmxjG96Rf/7CRyj2LuLl/EpWpfdTdmaQOUvXYXU4Zzqa4SY1b948QFCkJHFmIsQjcwh6MrRV+HAcEeTZgwwVFVI6Moiu2rGEYtR2ddBcmM+4Jrg9lOFoZjn+vC7aTL3UZ0qYl+2kzZxEomMRaxkctRDNQluhFbOSZJblAC2JtUTLLZgyGTBbSEweJ4pke3ANpnQXafMsbLF+nqm2oOkK3rSZ7kkrQgrSXujW3awztQOSsfgRQGP75AI85j0ICd91ZKme7OXQ/EXYBkcAGMubTVYICoYGcSQmALgYCiBqu5BCpWA8RX/cQX2mGZPUCFj6OCryqFKDnAvVYPHphDw2ivt6OdcmsaetVJeGyOoaA1knnHsGkuEr1rug8AEgyzq3haPdP2K23frWs1nMfz8oJjj1/avU2lfHLTtA1rNZ5meyPLe4mgwaqw414ha9bPnyIzMdzWAAQMu1oS5aRfFAP22lDqK2fO45YuHZpAUlKymseY50dgEbxzq4UJLHgM9Pzukxxqq2o8cOYEkn+a7/djSyzLd1IIWkV3XgdOShSsmAL8mQ28H2roMcHi/F5DnD+/rjvFSoMZ/VOEy7UDMu7k27QLfxRPsmtqvPM+woZjTPxIS7jIKmftS4BV0Kivz9jBFlnnUx1YkLqFJH9k7Q7paU9er0pBezbvIoNhnj+9vvRUmB6zWBZo1SX3IAX1ZwUIPBsmV84LUX+K/y+wkrVn5tIkTr4gjrjvVhS/s5mXsIh9uLWc2QVCfoD8yl8Hwjs+K9/EBsomr4FbTMBPuWbUKkz2COF2MWkiGlkKFTL7O1aGoC+kfOPsLSpUux2+3s2LED+TbTExluDFLqmMry+easIiwk2HhwB43mxdzz0Q/NdDTDTczlclFZXkEqJ4+aaAvnIlXYMh5eWOBFG1Yo0w6R1VQWdDXTWdqAFh2hcqQfqSg87p9knp7PiaHFmLQUpsBFVikpXhLLWasdpVPL0l+8irVnVU7FNdzFCUK6iTrbLjLSRqVXI2JzUNzXzfzeg+yTaVaGKzHpVoSioCRepz/XRJMmmaOXE1GzZAYWssKR4aTLRokawezP4OgYZNQcwp1YQaF1D5oNTiWSPNxrJWm2cDZQjteWRzozxLDbTllXN0PFBfiEk8aJfO5Sg4Ry8xB9Z/BqAer6YsTUGIg05nSWKhkmK1Vay+vosNspa+8moauociVepyRVGmbvQABSYTj9wyvX21mHyzmPjV4ze3rfYGuOypHJKF3x5C8+2ZELtdvh9A8gFbtGa8A7d8sOkL/xmS9yap6N47YGtg3v4bbYPKprzThc/pmOZjD8VOChDWiBOVT0nKO7bBm5oUkuTtrxDSexlJwnbXJQ3X4KKQRPbbqPZKfGB0PHKBtVKR7fw8WyOs6barg3spMuUw6vi42s9ryBUAO4Y1MnoWbMktOn5jJWvJMPdSmkVYXXinyE3Cl0kUZEdQKmMdpGV+Co6GPAmQEEzbV1mNMReKmSSFqjIL+DV3JfIr9/A/n1oyyYOM/h3DmM2jux6SqvalnKOreyiVfZu3AZvYF8tC6B1qVSUPcyq5IKWR2+5X2Yu7rfwD0R5pt5D7IuniCsteAhiyO5gHH7IF+33c5afycAFwIaejrNn/a/zhFlDr9+sRR7+Hn6CivptjtJivOYQxW0U86vmnbw2J5JHqx5kKdbnmYoOcSGDRvo7OyktbV1xtrZ8D/3l3/8a3RbltFiK+Ge4LNYR6z88ed+AyHETEcz3OQaFjaQtFqoS3WRRaNqcgHHqvvJaoKcixM4EUiHheaKSkAnb2KQguF+Xi1xUqb7cXeaGJV+8vPb6TeN0KZv4V5lP2fMOrrqYkVrEUciKpoKJ925FJvPYVXGGUoto7O0lILBQTK5ZXSlR7ChsCJ2G5b4SUzxJoSuszPPySxZiJCSoa75lFkkLxQoxLIale5xspMqO/wnScm5PBwOELAPooczTKZz8ESHeH7dJvIVSSITYqCgCmsyiRQKvokUE2kb41EPp2qiyGSIhWk3rZM+4uYBcjI2Zmu9RGxm/CLC7tQSxj1m/ONBHMkoF5oLULKS3CXD9E34iZq8cOSRt50TuaDwfmzZYQo1nczEqwjgu/1vMfXmyt+GWBBOPHa1m/2XdksOkL/691+FQsEPKtdQnumkqjHLSPQFFn/kz2c6msHwM+xz/ag161h66jgts4rIKGY+vMvNmUkVVIm/cifWgXwaJqPsX7YKeyLB5uP7CHk2MJF5GQT8l2sb86JtKDlZEkLDbO3FZK3DmYCgO0lXrpu7z+3jVDJBkT7AmtEJflimsoj1mGwnIOXlHmlDZrz8uHsFG5LPMWkuoqPSR8SeT9HhUWwSFCVLrr+LVMZEbW49cyJnSakaSvcAwzadQE+KSHgDW6M70Ujzrbvfj5oSuF8QmJ1jLCk6hEuH160ak5UNfPTFn/DV6o8QUSz85vgkTctCbDg2iC0d4GjufuweHxYtTVKN0Js3j6KmJuZH2njMtI1Fg6+iZcZ4Y8UWROo45lghNgFtohouPMdy3wcwqSa+dvJrLFmyBK/Xy44dO9D1y8zFabhhfP8rf0pt2QJ+VFnO3GwjC3edYtA9m7yy8pmOZrgFzJkzB1VR8VsUclLjjEVrSViyHJ1bhP2YQpGvmTF/LgvaL5Ky5mKZCFHT10t/bi7nHBk2pxQOxNbg9fXTbW9jY8aNJZNm1BQiRZaIdwNaj52+lCBYBSCpt71Gb3IhjiodISXu2CTWwdcZRefO4eUoeoi0bS626EmeqbUwSZLitJfulETGvJR7s1xQvWw2taCYs4iBY+hkWB5ahc/6JCjwfTXFbUMTtJRVEQmGsSh2Jj25RC0mqtvakJYsFqFyZqKQhdVdZKxuHH0dpHU3m4NtKCgolhFOJ3OpV0YIpnKYrCykz22n+mIr7WMmvKkKqgJJMq4UR0ecMNoM7Ve+wEdB/j0oipkPFgTY0fYDtue6eKw/SCRzmVkwyldD2Wo48FXIpK5J+79Tt9wAOZtOUzgwwjPLZxHDwbbDh5lNim1/8w8zHc1g+AVCFTjv2oJVdRBXRhksWEJtb5gndQeuUJqcmh3EqGX10An6PXZ2L1jFcJOHJTYn3vAIVWNNPD7rfYyrHj6YepWwMLNDbqAhtwUwk1FNZDSV3Mw4rzVvYKLsdT7UaWbConEht5SoowOQ5IUFTi3EqcF1lM5qpcNnBwEts+ZgS4yhv1LFRNJCSVErL+e+SHn/Voqq+1k40cTBnLn0uPvwpjWeckmq2jazlZfZtXQV3flFmFoEardK0dwXWJlUSGfhMc9HuK9zF56JMI/mPcT6eIKo2o7FkiEn0sCkbYSv2tex0d8OwIU8gS7h8727OCOqeehiBbbJZxjKK6Pdm09CHEEbr6GfAh42H+SrL/XykTkf5aXOl7g4eZHNmzczNDTE6dOnZ7S9DW9N1zNMaFkeqZmFBO48+jwXTAv5y//vr2Y6muEWYbVaqa+vJ5abT220meZoFTnJQl6bp6PEBMXxUwgJVcEBmqoXoCSD1Ay1o6VTPFaYZH62hLaeWoSAnPwWfOYQTylbuUs7QJNZZyx3Pvcc1DkQ1fB4M7RrLubaXgUkLqWc7vxSqtrbKEmMc1hP0pDMw6NXYEq1Yoq9TMKicsDhYJGsIavAZOttLHdk2RHQsAodb0ECOtIcyG0nldnAumw3HleS4HiKbQN5aJkUry1ZRb7LRzzZS6/fT97ICKOBPHLjVlrDucyNZ2mqsKMHW6lXi4kNWwiag+RkTVQTJEdksJNij2MpHbkeKlvb0fQMvSNLEYrAtHyYk4NlZE12OPhvV6y32ZxLYeFDlIk+ZHqc+cpFJjNZfjDwFnMer/9DCPVNHWpxA7jlBsiPffaLHFji5YS1gTuHdrM+NJtZizx4coypgQw3Jv+W2WgV69h4cA+t1XWoeoa1RxxERrLgiOEsOEfx6Qn8ySzPbn+QnOEQv3rmGeyp+UxkniVhs/Nd+za2jB+kx5fDkOKj2nYI1TKHvAmViDVFl9/DphNHuWBqZtl4lFmREN+pUJmnrgL7RdJJD9sVE9lkAU8Nz2NV+BniagHNtQVEbQEK9oZwqhlUNY090AxJF1UlNcwLnyapmsj29TFhlni6k0TCt7E1vBMTab5190OoSfA8P7UVeWnREew6vGJXGa1cxkdefIp/qf4IEcXKZ8YnOb1klPVHO3GlSjnm34/uLcJuSpJWYnQWLiD3wgXWjp/hP63beah3F6bMCG+s3IwSO4OWduNE5RTzaBh5FlfidrwWL185/hXq6+spKipi586dpFI3xtYJw8/6m7/4TRp9i2mxlvLQyBM4ehU+/6d/iKKoMx3NcAtZsnQJWVVhrhxASEnBxFLOlQ0Td2i4TmUImJJM5AcYd09dZdceiTGn4yL7ywLYVQ/LB+Jc0OeQV9DBRa0PT3oJmznOWXMWhInSiQVcCFpI6nC60IVLC1JpOcqF+BZGqz3YEgmkw81I9AIqgntGt2JKtZERLiyJMb5fY8OtW3CnTbSPeTAh6MxT6Mq42WhtBSnoyOxFYuf9k0vJtexG6JJv2xVmTXTz+vI1OIKjgGSoaD5ZRVA4OIA3MoZEcG4iHzmvG6moFI2EGYw7mZO6gF23ELD0sk/LZ446REu0kmixm6jDRHl3F6c7rXiiduaUR8gqgqaQA1pfg+ErT6NZXvYpkDr3B5wc7vw2yz0O/qN3mIx+mcMzqjdD4ULY/89vO9fy9XBLDZD/36f/iPFqlR8Xrmde8hzzGy2MhV9g0YO/O9PRDIa3pLotqCvXkx8cp6tQMOadzabTkh+mbZhSOoW1TyP1BrYON3O6vIiWonLSp8BSuAZz9Bx54SEerXiQrFC5S9lPWgr2iCWU5sQRwKhXErOYmD3ZzTOdGwgV7eeDnQptLjMJWy1xx1FAUBdSsapRDvdtoKa2iQ6vE1RJe1Ut9lgQfUc5wYSVkqJWdvpeY/bQVvLK+lkwcYEjnlo6PP3kxzV+7BNUtt7ONl7kjcUr6CwoxtSioHarlM19nuVJhWQGfuz+IHd37sYzHuLRvIdYG08gZD8Jv0LRSDUxc4iv2hdye/7UscPNvgRZs5XP9u7ngihnQVsV9oknCOYU01xYTSL7BurYHCbwsMnczKM7mvnYnE9yaOAQBwcOsnXrVsLhMIcOHZrJ5jZcxp/93oN4itbzVOFsVqYPUL/nPM75m/EWFMx0NMMtprS0lNwcP2a3h6pYJ+dD9SDMvN5QgPWsoCRwmJTFzILuVkLuUqzjo1QP9JA2mfhxIM5S3c+R8RXYbZOkfa2sV1Oc18txad1Migy9ZetYet7JiZiKozzJhDTTYH+BlHRSmWslbHdS1t1OcdcrnJAZtgfrEVhRhECLvUR7volzGiyQ1USVLImuVax2pTjpsVOphrAEUthahhi0juFKbKDMugOTTXIqmuBjnXYSFitnc4rIseeTzg4x4HVR3tnFSGE+ObqDMxOF3K0FGcnPQ+87QZm5lNL+KGEtjBUddzpBtR5FJcuxwkW0+tzMamohg0I0sQGzCfTFI7zRV4FUzXDwa1est81WRn7+XSy0hOgcP8f7PDF6E2meG5n4xScLAWv/AMbaoOnZa7MCvAO3zAD5G1/5D3ILHPzXwjU4CbN6/3lyk408+C831rQhBsPlFDy4Eq14CQvOHaO9cjH2ZAy13YZ9KIma3wvOKDWN5zDpkh++78NYuxN8sutVCicLIfo0QzkFvGBfz4Njr3HBWcBFKlnpfB2hlVI84iStZujNdTPvWCdd3sPcMSDxpeJ8p0Kh0ryUrK2bRMLJRk0hHa/gpYlyFk6+SBo/TXNLiVlzyduVwKUl0LQ05J9Gi+VRWllKffg0cZOV1GAfUU3i7IoTiW9kS+gNzCT51j3vR03Kqa3IjjGWFR3FqsPLDsFQxXo+9sJP+JfqDxNRrPzuxCQnGwZZfqYDb2IWJ/0HGXbNwmONoSsJmgsX4Wxr430jh/gPx138Ycd+zOl+dq/chIi2IvQs7qyFo3I+D6Seo6drAcXOYr5y/CuUlZdRW1vLvn37iEQiM93khmlP/ceXqK5Zw7/OqSKfQbbteJGjliV89NO/PtPRDLcgIQTLVywj7nTSkGwmnPEwa3IBu+eMIbKCQG8vdqmQk45yZvYCRDZEQSRIwXAfT5RZqM0Wk+nwE5EOCouaGdJGaOR2PqTt5LRFErNXcPchycGwhkmF455cis2NuNU+euIbaC6voGBoiEygmOZ0kBw0lsY2YYmfRIs3oehZnilyMksvxJSFnr7ZFJrhxULBZNrCHPcI2ajKLs9B0nIWvxIuI9/eBtEMF4ULX3SE59ZtJiDjJLMRBorrMWUyqFmdwOg4kYyF/rCP5rpRyCSZEzXRHvJgUlvxZK3MNvVx1uljlhrkWHQeo34n1myCguAAx5u9OGIwa844ibSF7pQLzjwO4aEr1ryi/NMImWKTW9DZ9yNm2S18vXv48jMLzbkbcmfB3n9825MAr7VbYoA8NjqEZbCX766uZ0zk8ODxXTRkndz5hb9A1cwzHc9geFvW6hyYvYaG82dprfIQt+bywf12dkbMCF1SMPs5LKFqNo6OcKBhHjGrjZoDrUwU3YeeOoQjEeVr+Q/h0OOssk3t8jqlVuB2ezFl03QUJJlwWFk52MiTg4vIehu5vzfJgYCFYrmQqGsnoLAsrKEpSfb0bqSutoketw+p6nSWz8YRGYU9pQzF7JQUtbHP8wbzR7bhL+hnwXgTx9yzaPUOUx7W+H5AUNFyB9t5kb0Ll9NeVDq1FblHo2rucyxOKUQz8LznXu7s2YdvbJJv5D/E6lgCZ3aUkXKV6u48UmqCrzur2BZoAaDTO0HK7uJTnYfolPlYumvxjf2IkDufpop5JFO7UMfrSWKhTgvy4qELPFT1SZrGmni542Vuv/120uk0e/bsmcHWNrxpZKCLoXSYr9fOJSsUPnTsewzGKvmXf/jrmY5muIU1NDSgKApFWgpPOkQ4PJ/u/BS9RU4c+wWFnk5CuTlYZQYpVCyTSeZ1tjDk9XDao7A1LNmf3kCuv4duWzvr0zlU6IO0mhNIJGHfaqzdXnpSgskqnSyCRY7nCGaq8FSa0IUgEBxC63uBUXQeGFiNIE3WUoY1cpTXa6z0EKI2W8SQniU1VkaVN0uT2c1GUzuqPYPW00hGpFkUWoHN+WNQ4VmSbBsI01paQTgYx6I6SNgtjDtsVLe1kXFasAqNMxOF3FvQS8KVg9ZzFpsaYGN/D0kliapGGIk4mKePk5UazVX1tHjdzDrXSiitoaZX4rFJMrUT7O4rRmbTUzNaXIHTWYs/dxMbXFl2dr/ERwscnInE2T9xmQ0VigprPguDZ6Dt9Wu0BvzP3PQD5Gwmw8t/8xWeXlNBs6mG97e/ytqhIhbeswCfv3Sm4xkM/yNCCNz3rkFzFWOf6KarbBX54yGOTdjJGUnhqDhOUstjWftBEprC97Y/TLpV4cHwBUrGzPjHX6WxdB5HrQ08HH6RFs3PURZym28PCCeFE7k/vXCI51iU/sAbfKBLQ5M63y1TKbLMJ2MdIh63s8qkk4zMYVc6h5qJV9F1H+fqK4hbcwjs0HGZY2hamnjRISyRUvJr85gfPkXMZCM+0k1SkTg6o0RSa9g0vg/LpVuRnwOzY4zlRUcxS3jRBX3lW/jYCz/ha1UfJqLY+P2JSY7X9TGvrRd/bB5nc4/Q5J5PwB5GkuJC4SIsfb18qH83jzjv5kvNR7Gku3ljxW0Q6ScjBnEn3RxnHr9hfoVdx4up9dXy1ZNfxePzsHjxYo4dO8b4+FtMWm+4LjKZJN/98b/xVMUS+rQAv9L1fUztCn/yf/8/47hjwzVls9mYX19PPDePeZHzNEdm403m8exiB6Z+hWLLYYSE2UO99BfOxRzup2RyBEsyzneKktRnymjqa0AROoHCZjzmMK+yjnXaIXq0LL0la3j/ngQHIiY87izNmocayxuoIoFZr6GtsIqKzk48aprDepyGlI8c2YA5eR5T7FVSJsE+l5cGvQohJSPtq1ls03k5oCGlIJAXQ++Dvf6zpLJr2Z6KkuMMEQsmaRjzY8qkeHXFevJdVsKJbgbzS/CEQozn5OKf1OmI+rAkNZoqdPTwAIvIo3s8lxFbJ7lZK/VqH0GXhRJlgv3phfTkuigYHcIdD3G6sxpzSqdw4SijUQ9BNQeOPgqp6BVrXl7+m5hIstQWR598jYBZ41+7hy//5IaHwVUEe//pGrT+/9x90rTxAAAoAUlEQVRNPUDWdZ3vfvbPeGVDKQecS9gWfIMNzX6c1b3UrLxzpuMZDO9I4LY61Kp1bNm/i5ZZJWRUCw/tddE8AWhZfJVv4Oq00TARZ/fqtZjSGe7au4OwezuR7Kuo2Qz/mnM/JckhSj2jIAQDJgtmRyWuaILWwhhDHgfbuo/wVCgfl9bP9sEJnisx05BYTsTzMkJqrI+aUESaHV2bmTO7kQFnLrpJp6u0BufkCNqhQgYiDkoK2znqOszi8S348wZYMH6Bk44qWn2j1IyrfCdfobz1fdzB8+xbsJzWkgpMF6e2ItfOeY6GpCCUgh3ubWzvPUBOcJxv5D/IiliC/HSIzlqF+mYzEsk3nAG2BZoBSa9zmLg7lw91HmVQz6FnuIHSkR8Sc/hprF1AJr4fNTwHBYGPJC2tbaz3f5y+SB+PNz/Ohg0bUBSF3bt3z2yDv4dJKfnyP/8Zb5Qt5bSjiofGn6Tw6Cgf/csv4Zg+OcpguJaWLluGrqrMYQBF6uRPLOPQ7FEyZoHnWJo8LYnJrHB29hyQKRzROPUt5zhcnItm8rKiJ8IZuYCColYumnpwpJZyr7KfE+YsWdVDYaia9hEbCR3OlTiwqAnm2F6nPbGasWovllQKVVEZC51GAvcNbUTNBskqLiyJEX5cayUtMxSlXHRFzYiMlbF86Mh6ud3cDEIyED2IxMoD48tw2l5ESPiORWfuWB87l63G2T8ICMby6khpGsX9feTEJxEIzkwUUl/bhW6y4unrJpFxsS14gazI4jIHORbNp16MEM06GKisptvrpLqpld5JBXe8mmJvBr0gyv5+HyQm3vYqeF7vUryeZWz3Kjxx4Tt8osjHrrEwTZH4Lz5ZM09tRe7aB10HrkXz/4/c1APkb/3OH7JvYwmv+FazJnyY9SdAVQ6x7rf+z0xHMxjeMcWsYt60EXsGhh0x+guWM68rwhNJF65QmkDNKyREPZsGjzHstPLcyq1Ez5tpsNnxh+NUDh3h1ar19JgK+WDqZfpxs5vVrAmcAUx44zkgIGLTCJ1yMlT0Kh9vt5JWFH5cbsVrrSRlGSUZtbLEkiIems9BxUnZ5OvIrJezDVXELT5yXlJxWKa2Io8X78Y2MRvfXA/zw6eImO2Egl1kBNg6o0QyK9kQPIxNRvnWPQ+ipv97K/KyomNowMtu6Cp/Hx9/fmorcljY+MPJCU5W9lI8PEJ+uIGLOSfZ415JsXMSSNNYuABtZITf6H6JR5138ZXGE5hT7exdthERHSfFRZwxP+eYzeecO3h8n52l+ct55MwjqDaV5cuXc/r0aYaGrnzsnOHqk1Lyt1/+I05WLOeQp4a7Q88yf9cFNv36nxAoNmYbMlwfJSUl5PhyMbk8VEc7uBCaT9KssWd+PrZjCkUFh8hYzNQO9JKw5mAfG6ditB9dVflhfpzF6QCHxlZjMUdRAhdZqel0yXx0cy8xkaWzcjOrzjg5HtNwlyYJSgsN9pfQMVHm9jDu9FLZ0UbhwEFOyAy3j9eAkouqRzDFXqQv18Qpk8YS6sgKyUTbBtY60xz2WMlT49gLUphaJul2DGBLbqDedBirPUv7ZIIP9rhJmi2cLKojx5lLItlJX66X4t5eBkrKyElZOD1eSJ0Sp6PES3bwLPNMpWSHPPTZe/HqKnPECBarjk/E2GdeRHuuh4qODkzZFG2ja1CyEtfyYVrHCohYcqZO1nubmSfKKz6NXSSpUIYIJI9iUxS+3vMWW5EXfwwcAdjz99eg9f9nbuoBctPyPJ7zr2d59DhbDkWxR/Zy95e+NdOxDIZfWuEDyzCVr2XLgZ201dQhpGT5MRuxkSw4I9gKmsk9E6YgnuWVLXdjjyT59IEfkVHWEOQn6IrKo557WBxpQroFGaGhmUdQrTX4xzP0+KP05ri4t20vLyUFJelxNo0EebxMY3V8LSHPiwhp4vaYFUXovNS5jTm1Zxl0+tFNOj2lNbjHh7EeD9AfcVBS1MYJx3GWTW4iJ6+f+eMXOWWvpMU3zrxRhe8UqNNbkZ/jwPxlNJdWYrowtRW5Yc5zzE0JxlKw27uB2weO4h8d49GCB1kaTVKeitIyHxafS6HpFr7jMrE10ApIRqx9hHNLuKv9JKGMnQOR5SwZ+h4JWy7HFixFjx5BjdVgIUsyo6CNt1PGQ4wlxvivc//F2rVrsVgsvP76zB7j9l4jpeRLX/48h2atYHdOLVujr7D0tRMsffiPmLNkyUzHM7yHCCFYsXI5CaeLhmQzkYyXytB8Xm6IINKCvJ5eHLqgJBzkbO1iRGoEfyxMWW87T5fZqckWY2+3MSr9FBW2MGga4Wx2Mx/UdnHSrBNx1HDHMcnhSQ1NgWMePz6tjwLzWbriG2mqqMQfDJIKFNCeGsKLyurwJsypZtREK0o2wzMlDnJ0B66USvdIATkavF4EIyk7S5y96CmV/da9ZGQZn5qYTcB6ChHP8prFTF5kmMe3vA9/dIKkHmOgbAkSgW98nKLgKEld48x4Ifb5nUhFo2Rokv6Ym6Xx86goFJn72JUtZp46xGAqj8GSEkIuM5UdHTT2SXIjfqrzE0hnmlNDNhjvhAvPX7HmuTkbcDrncIdX8ETTozxc6OWpoQkGkpeZetNsh1W/A207off4tVkJ3sZNPUC2tQTZPrqbrQfG8CWO8aGvPjHTkQyGd8Xkt+Hc+n7KBwbpLhSM5s5jy2nJ40kr5pROSe2TZOQitnYOcaEol+NVc0meFnjyFuOMD1E1cpHvVN1DSHVwn7qLcWnlFbGRhf5eFDXAaK4LXVFQRZrGc5UMl73Ar7baiJo0flDhweoIkDaPk4qYWWyJEQvN56DmpiyyA7JezjRUkTB7yH1WxWGOomlpgqWvYw/W41tooiH05lbkdlIK5F2MMqkvY/3ICewywjfvez9q5r+3Iq8qPIYJeM4JLWUP8vEXnpjaiqzY+cLkBKcL+3DFQhRO1NPhbeKHzvdR7Q4CGU4XVKCEJvlsx7N8y3En/+dUI5b4WfYv2UJMCOL6QezhEjoo48+cr/LjA7Cx+Ha+1fgthtJDrFu3jubmZpqarjyPp+Hq+dsv/QW765ZzyDObu0PPsealw6z68BdYvHb1TEczvAc1NDSgCoV8q8STDREON9BZkKC3yIVzp0qhr5mEx4WiquiKGXtwkvquZsadDg7lCG6LCPYmNuL1DTDgvMjqTAG1spvzlgRZIektfR95zR66kgrRmjRpqbDI/jwxPZeCMhsZVaWktwtz/4sMSZ0P9C1DSg1pysEaO8jBaivNIsJCWU0EnWjXCpblZDhjd7FU7cfkTWO+2ELINE5x5C6qHU+gmiQHQnE+1iEY9OdxwV6I25JLPDtEb66byo4OhouL8WVMHBsrYY1lgqHCPPSeY8wxVRDosjBoHcIhJZXpSUrUKA6S7PKuodnnpaapBaSkc2IjipCYVwxzeLCClNkNB6485ZsQgoryT+NTkrjSbZSlj5GVkn/vGbn8Lyz7dbDnwqt/PiMzWtzUA+TC8Q4ePmInTz/Pw/9oTOdmuDXkPLAI1/seYNGZA7TMWoAlnWDV3iosgylEfj8WfwdFZ3swZTJ87cGP4xqJQb8Zs76O9Wd3E7M5+a5rO3eM70XP6kSFHaejG6vnQWrDDzPiidHh93JbzyFeysapyvZzd/8EPyjXWJzeRtz9GkI3876IDU1J8nzzB6hdcIJuTy5Zk+RC3QJcE0FcLxUyFJ+aF/ml3OeY5UmRU9fBouA5DrprabG3URFSeMYhKW+9h7t4hsNzF7Nv4TLMTQJTh8KS+Y+zUk8TSsNjRUvZEjrL7NZ2/rn0wyyIJrk9GqJ5mWTFqQmsaSdPeYdZFgihKjohbYBB/yw2tJ3GGY3xz+rD/Fr7v6GrKi9sugsxeRqR9OHWdU6mq3hI7iAxeBcW1cJf7f8rlq9YTn5+Pi+88AKxWGymm/09IZ6ZpN0e4P2jT7Dg5bPc/Uf/SMOqlTMdy/AeZbPZmN/QQCKngG1WJ+3hOjzJPL693oM2KigfP4EqoaGvg/Ozl6NF+ykeH8IZDfHvFTr1mQpGWstJSCtllSfQraO8Ku/lIdMrnDRnGQks5eE3FHaFNDwOnaPeHMrNx3CoI0yk1nG+YhYVnZ2YXHYO6GFqs06WJ+7EHD+JGttPRpH8sMxPlV6IJSto65rDbDM8Ua4wmbGyLNBDJqzxquM5UnIenx+rpth5ChFOs1dYKIgE+dY9HyAvI0hmw/SWLQLAHwySNxkimjFzNFgKS1qRikJV7yADsQANsWYs0kShtZ3dSilLtD760vmcqZ5Dlgw1ba2c6LLhiuVQVxlGuNMcHXZC7xE4f+X5iwOB7dhsZdyfo/H42X/i3oCD/+wdufyxyBYXbPlr6D74tsc4Xws39QD5t//tSZZ8bhMfMA6rMNxCzKUu8v/oM2z9lQ+hrypiOLCA2bGFDMX+mLHJQqzei2jZQlad2YfQYMCew+ce+0+cymZW7L/I5tP7eETczYVsHUviMKw7eFFsYqX3UdwZnUPzooy7ddJ2ndNnq+kt/zGfuahhzkr+3zwPs8wLSVqGiUYd3KumSSZK+Ub/RhabHyeulHFxTgFjvjIKdoTxTWQRShZ/5WFa01HKVw6wXN+PRU9xMSYIauPMvpjggmkRt/Wep1y28/cf/RRBZw7e76qoSoL7F36DkozgWBaeqvwMX3j663yz4H5O2uv4q+A4QXsH0RKY1VfBoKuTv3Tfxpb8qUtQny4QZLOSfzj1bXaxiPzmSspHvkdP8VwONawhHnkaJbiQFBYq1UlGz51hre+TnBo5xVdPfZV7772XWCzGE088QTY781duutUNdSX53KtfpmpHB5/8h29SVFkx05EM73Hr1q9jef1qfi3twqGmMQ0+QEvB5+gvCeB7WVLubiHlcRJ15KArFtyjEzS0ddEWyOHJfCvzxkZ5MX4Xfn8v/f4jrM3MYikXuWCdQBc6QyUfxXPUSVtCIThX0C29rHc9ykSmjNyaQpJmM3MvnCc5+CydMsvvdG3GpvtQZQJb+DVerLNyVkuxJjOXkMgy1ngXm/PT7HR6Wan2YQ8kkI19tNvP4ol+nHtMT2CxZjk1EuWhdhPjLg/P1s0nz1ZEWB+gsyCf8u5uxgqKyIvB0WAJc0Sariov+uBZ1mRKUNsUxs1D+HUTc7JdWDRJngjzsmMTh8rLmHPmHLZUnJMt6zAhydvWw5HBCialDZ7/gyvOi6woGjU1f4FPibHGFiQx+K+4NZXfa+omltV/8RcWfhhKV8LLX4Bg2zVcEy6T9bq+2jUQKJw10xEMhqvOlJ+H78EHeOD991LzyD9RuvIhNm/4MIeOPszxPAfusn9invYjIj4/j274IH02H+vPDDNUUMDvP/YjPtXyNC9nPsjsjJ+eaB4ZVE5Y/ZgqHqdh5H6e3NBPxJ9gdfAw58dTpGr+g4faH+O818TZwkXYctqQ6FROOCg2D3OxfwtNLo2osxt0J/vXLEZXTOT9s4fJmCAnZwAt4cOctlNw10W2Db9Gu7uIM4kulHSMA/Ew+V2/w+9OPkLapvH5P/g8iUkHnicU3HkXedDag1WHRx0F9Fau4/Pf/Xc+Nf+vSQoHH4tFeK22lbqJJEXjszhauIdvBW5ntnuErKpzoKoM18gw/3Tk3/iy5f389r4ePOF97F++lbNVdSTjL+OeqKCLEj5oOU7T3ihr8+7j2+e/zYvBF7nrrrtob2/nmWeeMQbJ19i/P/oNAg2/wme//hhWh3Om4xgM5Obmsu3BzfjKvXxSuKkJ5PHXvTZGNn4GJQFl5uPc5k6wquUUJ+euoa9iJRWxforGEnyvzsugTSV7Lo8BvZCa2gO0us7QmvkVHjP9NW4lSNTt48O7JC8NWjBrkpfLnTi0Fkotx2lJ3Ef/ojoCo6NURkZ5I9FOjtT4497fxpxsR0m1YkmO87+W+/HrLooyHi6M+7AP19Ndr9Oa8fFAbiMAp4afJyYUPjr6q6x0fgeR1vlmPMnm3gleWLeZLlcOmtDoyS9g0m5jwenTSJcbs1R4tncuy+ovkHD7sTftoVyfw5KOFnSRJcc0STAjWKn1oUuVH9XdR2uul+X7jzAQ8hDqW0qhL41r0wA/6ZhNNjYO338/JEJvWfOAfzNFRR/kNlcSZfwVVnKAxkic323qIqX/3CBZUeDBb4CiwQ8ehvDgtVwdfoa47JVMZsjSpUvlsWPHZjqGwXDDkRkdoSkMd3Xw8NNnWFf3BLdXbqDa/BAvfOsM/+aKU1TwDF+8cDvJkEar+Sge02H+X/zX+Fz2MTKKSotvMQHPMKMd93Gy9Aek9Ua2XcxBqjZsBfOItJ9h57ytbE3m8ECyjEedT3DcPYm01dPeVURMt/CBqv9iaPJBqib7yBscYP3eXYz5rYx+Lo3bE2Wwt4asc5gD56xkWtezo3Ad6wYbWR7az+v3f4Iv9qTYu+DHfMn2BYqDQ/zfr/09uaYgR8r+DwNOM49bdUwqfKP/27ziKuHp923DFh3Gkvw7xjNwV0cN+3OSDHu6WTGwlPVNXYwk7LjiWdY0d9KXk8+fL/0k2+QRnti0gAnvEpae2sea08dw5C5gzDVJBT2cz+TSuShCU2Qv98+6n/Wp9ex7Yx9VVVXcd999uN3ud9xGQojjUsql16D5b1hGn224VWTGEwiziuowkWyfxFzqIjXYxOmmjxJWJ3Hv+TT7Lh7kYn2WCq0C07CNb2+8E3vwEYrGlpDrGOPBmsdJhD2cOraV72SWcXtwnHlqId7gP+AO9vLYp6AjpfJ3XaMsSjt5Nvh/ARVz13PMGm5iz4a1aMom3q+4ec17ga8U/AsR5xYSng+xeiDL35yP8JzlKFmyLKg9QlBr5Y7TY7QrHva0zMKSD9scn8QlWvktV4yTE0txVrjIy1No8tj5xI5XyWs/iDdrYfHFJrKqRtiscaoyD4cpweb8FuK78xBp6K9bSYe/k+68RYS1JL3JPFxo7EpXU6AP85f7/pOUP8CpxYtYXLMXR2En/a0ubMctPFB4ARGoQ3zwu+CvuWy9dT3JqdOfYmz8AM9OaDR7PsspZRXrfE6+OqeMQsvPXeSt6wB89yFwBuD9/wVFi951m79dn20MkA2Gm4yUEgkoQgCQyWRpf7aN/+jro/T8S9z5/l9lUOnnteP7cTta2eNO874TLvzdEZrLirGaq7hbr6U1dIyWsQMMzv4w8byTTFpeYoO1kt0ty9ky0sYZx2GO1/wm7nCEikk7Rywp7oqM4upJcGLZHHKjQSp6utiwdw/nC6qxf6SPpMtCd0sZPyxq4o4LhXQNLMYd1flk625G132S5xemeX9/nBOLD/BP6mdZdPY8X/zeI5y7bwVj4XWMmBNkJ8pwqVFWhp/hiFnlX+/+GL/R+k325R+lLS2oDfnJhlRaS4ZYMLCSh1oaaYvkYkumWdfcR1ZR+P0Nv8s/Xvwaf/TpDxKKaXzgxTfQVQVLbgMRn4Im0lTKTg76bexynyDXlsPniz7P8TeOY7PZ+L3f+z00TXtH7WIMkA2GW08qNcGRo/eQjm6kovrj2PPsHHn5ftadH6Yv9DG6RC2P1LtRZC/bx1+gsqGJcMRL40/q2XT2Al1Vq3lmxTH+aHyC10vm8H3HOW4bK2Ruj59swkGCh1CkStraTdzTjdAy3GHzYo06+UTFblKcI25bSVloC791Ko9aZ4JXLKdIkqa07DRhpY0PtQ5yUfFxsKUKd3WSreJjPFbyPK/FltE9dyOaopKfyBLPxvj7R77OeW+GFdalmI99H1MmzaTVwunqPJKaxgPFF0kc9ZAdTpAtXcyxKjedBT4yQqEvm0NSqhzJVKDqaf7kxGMEbDonFy2kqvIkReVNxKMaeqONzclubOhk5z2AacVvQulymP7MelM2G+P8+T9heOQlelIqP0xv5bzr1zEpKr9SmMOnS/Motl4yUO45Co9/DCKDMP/9sOBDULpiasaLX4IxQDYY3iNioRTNRwZZsLkUIQTZbAJFsSCEIB5PMN7VSVtIUlFVgjWYIvT9M6gJyeiH7ZSWN5COjPL0U39HwRkLx50eCuubCZ7Ip7kmj/Lxl6jUUoTzvDRkOul9sZCf3H4vfkXj4eZvMaBux+86i5aMMjoXGk25ZE9vYHbyBK7gKEOBzSxylhGP9bPP00VCU3koU0Fu9w9JnYjwzNZVmKob0Rw22po+TF9+muK+IywfmqQ+eZw9OT4S5QHGPCFeFyMsaPHgiziptK/BXZXFOrqLUDKD7Klhtmk2s39zE94Tj2AZfJJeVfD3BYtxn7aQMywQDj+mgjKCZoU4Gj/Gjzf/MH+6/H9xW7mT0dFR6urq3nH9jQGywXBr0vUkimL56f1EJo41EQF7Lp2NY9g9ZpzRFOTZiLT+B2MyA30FZE6+yutdNgLBFtLbVtFvcxDv2IvTrOBKrccSGmBoIktFahZVwR/QvnQVZ91+vPYeNutm+lUrX1eC9PiOg/DwwMgfMHsyTL5QaNFHGFInMc1uxHZRsL3kMMfC92N3uPlKwVr6M1A48h2sikpvwX1MuqpY3xflTx7/LSzjPvT71tHa+TK5xyX+8TjHygvJUWNsLO8iJusZbJVYgjGcm/83L4z8gMkyE3Elnwgm4hYHp8N+enUf80daeTi+i8zcIoJ2yYLZe8hYEnQ/Ucxy6xB1OcNY3MXw2dNTl5H+OVJKhoae5WLr35NJDRDU6tiV+688NzLBs4tqWOxx/OwvxMZg75fh2DchPX1ytasQPvk6eN7ZPOrGANlgMFyWHs+QaBnH3hD472W6jqL896kJUkrEJd/6s9ksqqoSO9tItL0NvaicwJIGYqEkfbEJZufnIUUWXVeQyQznX9+H7pbkL19PwKwQHo8yPhLEX5LAaa9DSEGyq5sjjTuQi6rZULaR/f37WVm4CiEhOhQjlhnDnOvEKuKcuPi3jIdSBNpKcRfWUr3mTkxOG3v6Rtgz2cM9rRqzN8/F7pre6jDWjjzxGGL9HxMTglBXL5Ojw9jcczC7k2Q1E4f7k7x4dpCHlpSwvb7gl66nMUA2GAw/T0oJUiKm+1U9mwYEodgwjkSaoIhgGtVQCnzYbTkMdbUyduE0/RWzOZPI8KDFy9OvPopgBH95A66gi6hzCF3NwTcUR1uVh3v/LroTczF5gcggE+Zq0pF2gs5JfK4SxMVOYoEAirWMerUD+9AFShZ5aPIs4fSxYarSIwTKF2Fuu4Bzby96ncp4zQgDqQWI1Gx8c71sWFrC3vZG0rGT6LUfY0GiiOONA5xPqjxU0s3c9Q8xPDJCbiCP5GQjocw4+9/4Jv7FH2CDvRQKF7xNnXQmJo+TTAxQUHAPI6k0AbPprX8hFYWOvTB0FsY64a5/mroC3ztgDJANBoPhOjAGyAaDwXDzeLs++6afxcJgMBgMBoPBYLiajAGywWAwGAAQQmwXQlwUQrQKIb4w03kMBoNhplzTAbLR2RoMBsPNQQihAv8K3AHMBT4khJg7s6kMBoNhZlyzAbLR2RoMBsNNZTnQKqVsl1KmgB8C985wJoPBYJgR13ILstHZGgwGw82jGOi55H7v9LKfIYT4DSHEMSHEsZGRkesWzmAwGK6nazlANjpbg8FguMVIKR+RUi6VUi4NBAJv/wsGg8FwE5rxk/SMztZgMBhuCH1A6SX3S6aXGQwGw3vOtRwgG52twWAw3DyOAjVCiEohhBl4GHh2hjMZDAbDjLiWA2SjszUYDIabhJQyA/wO8ArQBDwupTw3s6kMBoNhZmjX6j+WUmaEEG92tirwTaOzNRgMhhuXlPJF4MWZzmEwGAwz7ZoNkMHobA0Gg8FgMBgMN58ZP0nPYDAYDAaDwWC4kRgDZIPBYDAYDAaD4RJCSjnTGX5KCDECdL3DX/MDo9cgzi/jRsli5PhZRo6fdaPkgBsny9XIUS6lfE/NVflL9tlw47T75dzI2cDI924Z+d6dWynfFfvsG2qA/MsQQhyTUi6d6Rxw42Qxchg5boYccONkuVFyvFfcyPW+kbOBke/dMvK9O++lfMYhFgaDwWAwGAwGwyWMAbLBYDAYDAaDwXCJW2GA/MhMB7jEjZLFyPGzjBw/60bJATdOlhslx3vFjVzvGzkbGPneLSPfu/OeyXfTH4NsMBgMBoPBYDBcTbfCFmSDwWAwGAwGg+GqMQbIBoPBYDAYDAbDJW7qAbIQYrsQ4qIQolUI8YVr/FqlQohdQojzQohzQojPTi/PEUK8JoRomf7XN71cCCG+Op3tjBBi8VXOowohTgohnp++XymEODz9ej8SQpinl1um77dOP15xFTN4hRBPCCEuCCGahBCrZqIeQog/mG6TRiHED4QQ1utVDyHEN4UQw0KIxkuWveMaCCE+Pv38FiHEx69Sjr+fbpszQoinhBDeSx770+kcF4UQ2y5Z/q7eU5fLccljfyiEkEII//T961qP6eW/O12Tc0KIv7tk+TWph+Fn3Qj1FG/dl39RCNEnhDg1/XPnJb9z2fXjGmbsFEKcnc5xbHrZjHzW/Fyu2kvqc0oIERJC/P5M1+5G6YffQbbL9s1CiAohRPySOv77Jb+zZHqdaJ3OL65hvnfcntfqvf0W+X50SbZOIcSp6eVXt35SypvyB1CBNqAKMAOngbnX8PUKgcXTt11AMzAX+DvgC9PLvwD87fTtO4GXAAGsBA5f5TyfA74PPD99/3Hg4enb/w781vTt3wb+ffr2w8CPrmKGbwOfnL5tBrzXux5AMdAB2C6pwyeuVz2A9cBioPGSZe+oBkAO0D79r2/6tu8q5NgKaNO3//aSHHOn3y8WoHL6faRejffU5XJMLy8FXmHqohL+GarHbcAOwDJ9P+9a18P4+Zk2uSHqyVv35V8E/ugyz7/s+nGNM3a++T65ZNmMfNa8TXsOAuUzXbu3eL9f9374HWR7q765gp/rOy/5nSPTecV0/juuYe3eUXtey/f25fL93ONfBv7qWtTvZt6CvBxolVK2SylTwA+Be6/Vi0kpB6SUJ6Zvh4EmpgZn9zI1UGT63/umb98LPCanHAK8QojCq5FFCFECvA94dPq+ADYBT7xFjjfzPQFsvhrfPIUQHqZW3P8EkFKmpJQTzEA9AA2wCSE0wA4McJ3qIaXcA4z93OJ3WoNtwGtSyjEp5TjwGrD93eaQUr4qpcxM3z0ElFyS44dSyqSUsgNoZer99K7fU29RD4B/Av4EuPSs4OtaD+C3gC9JKZPTzxm+JMc1qYfhZ9wQ9bxCX/5W3mr9uN5mom+9ks1Am5TySldSvC61u1H64f9ptiv0zZc1nc8tpTwkp0Z7j13y91z1fFdw3fvKK+Wb/uz+APCDK/0fv2z9buYBcjHQc8n9Xq7cyV01Ymq3/CLgMJAvpRyYfmgQyL8O+b7C1GBDn76fC0xc8oa79LV+mmP68cnp579blcAI8C0xdajHo0IIB9e5HlLKPuAfgG6mBsaTwHGufz0u9U5rcD3W5V9j6lvzdc8hhLgX6JNSnv65h653PWYD68TUoTVvCCGWzVCO96obrp4/15cD/M70bu9vvrlLnpnJLYFXhRDHhRC/Mb1sJj5rruRhfnZgcqPU7k03Yj98OZf2zQCV05+pbwgh1k0vK57Ocz2zvZP2nKnarQOGpJQtlyy7avW7mQfIM0II4QSeBH5fShm69LHpbybXdN48IcRdwLCU8vi1fJ3/AY2p3R5fl1IuAqJM7cb6qetUDx9T31QrgSLAwVX41n+1XI8avB0hxJ8DGeB7M/DaduDPgL+63q99GRpTu09XAn8MPH61juMz3Hwu05d/HagGFjL1ZfvLM5eOtVLKxcAdwGeEEOsvfXCm+xUxdU7HPcCPpxfdSLX7BTNdr7dymb55ACib/kz9HPB9IYR7BqLd0O15iQ/xs1/Srmr9buYBch9TxzW+qWR62TUjhDAx1aF+T0r5k+nFQ2/uzpr+983dttcq3xrgHiFEJ1O7MTYB/8zUbiLtMq/10xzTj3uA4FXI0Qv0Sinf3PLyBFMD5utdjy1Ah5RyREqZBn7CVI2udz0u9U5rcM3WZSHEJ4C7gA9Pf0hc7xzVTH15OT29zpYAJ4QQBdc5B0ytsz+Z3rV6hKk9MP4ZyPFedcPU83J9uZRySEqZlVLqwDf470MBrnvu6T1jbx4G9NR0luvdt17JHcAJKeXQdM4bpnaXuGH64cu5XN88fehCcPr2caaO6509nePSwzCuabZfoj1nYjymAQ8AP7ok91Wt3808QD4K1Iip2QrMTO3uefZavdj0lqb/BJqklP94yUPPAm+e7fpx4JlLln9MTFkJTF6yu+eXJqX8UylliZSygqm/eaeU8sPALuCht8jxZr6Hpp//rr9JSykHgR4hRO30os3Aea5zPZg6tGKlEMI+3UZv5riu9fg577QGrwBbhRC+6S3iW6eXvStCiO1MHYpzj5Qy9nP5HhZTM3pUAjVMncBw1d9TUsqzUso8KWXF9Drby9QJUoNc53oATzN1oh5CiNlMnUwyynWsx3vcDVHPt+rLf+643fuBN8+af6v141rlcwghXG/eZmr9b+T6961X8jNb7m6U2v2cG6Ifvpy36puFEAEhhDp9u4qperVP5wsJIVZOr78fu+TvuRb53ml7zsR7ewtwQUr500Mnrnr95FU+m/R6/jB1NmozU98S/vwav9ZapnbRnAFOTf/cydTxq68DLUydIZ8z/XwB/Ot0trPA0muQaSP/PYtFFVMraitTu73ePFPfOn2/dfrxqqv4+guBY9M1eZqpM3+vez2AvwYuMPUm/g5TZ9hel3ow9SExAKSZGvz9+i9TA6aOQ2ud/vnVq5Sjlanjwt5cX//9kuf/+XSOi1xyNu+7fU9dLsfPPd7Jf89icb3rYQa+O72enAA2Xet6GD+/0C4zXk/eui//zvR6eIapD/fCt1s/rlG+KqZmATgNnHuzTr9Mv3KN8jmY2uvmuWTZjNbuLd7v170ffgfZLts3Aw9Ot/mp6T7q7kv+n6XTfVcb8DWmr4R8jfK94/a8Vu/ty+WbXv5fwKd/7rlXtX7GpaYNBoPBYDAYDIZL3MyHWBgMBoPBYDAYDFedMUA2GAwGg8FgMBguYQyQDQaDwWAwGAyGSxgDZIPBYDAYDAaD4RLGANlgMBgMBoPBYLiEMUA23HKEEF4hxG//3LKXhBBXvN69wWAwGK4/o8823IiMAbLhVuQFftrZCiFsQK68ZEJxg8FgMNwwvBh9tuEGYwyQDbeiLwHVQohTQoi/Z+qCKrsBhBBfEkKcF0KcEUL8wwxmNBgMBsMUo8823HCMC4UYbjlCiAqmrjBYP33/q0xd6e80cACok1JKIYRXSjkxUzkNBoPBYPTZhhuTsQXZ8F6wBtgHTAIJ4D+FEA8AsRlNZTAYDIbLMfpsw4wzBsiGW5oQogrokVKmpJQZYDnwBHAX8PKMhjMYDAbDzzD6bMONQpvpAAbDNRAGXNO372C6UxVCOAG7lPJFIcR+oH2G8hkMBoPhvxl9tuGGYwyQDbccKWVQCLFfCNEIDACfmn7IBTwjhLACAvjcTGU0GAwGwxSjzzbciIyT9Ay3LCGEBdgvpVw601kMBoPBcGVGn224kRgDZIPBYDAYDAaD4RLGSXoGg8FgMBgMBsMljAGywWAwGAwGg8FwCWOAbDAYDAaDwWAwXMIYIBsMBoPBYDAYDJcwBsgGg8FgMBgMBsMljAGywWAwGAwGg8Fwif8fO/hET5c+1dgAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def L_(V,r,CLdelta=0,Rhodelta=0):#单位m/s^2\n",
    "    Mach = V/sound_speed(r)\n",
    "    return 0.5*R0*Rho(r,Rhodelta=Rhodelta)*V**2*Sref*CL(alpha(Mach),Mach,CLdelta=CLdelta)/(m)\n",
    "def D_(V,r,CDdelta=0,Rhodelta=0):#单位m/s^2\n",
    "    Mach = V/sound_speed(r)\n",
    "    return 0.5*R0*Rho(r,Rhodelta=Rhodelta)*V**2*Sref*CD(alpha(Mach),Mach,CDdelta=CDdelta)/(m)\n",
    "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(12, 6))\n",
    "axes[0].plot(result_tk*np.sqrt(R0/g0),kQ*np.sqrt(g0*R0)**3.15*np.sqrt(Rho(result_rk,Rhodelta=result_Rhodelta))*result_Vk**3.15/1000/100)\n",
    "axes[0].plot([0,np.max(result_tk*np.sqrt(R0/g0))],[Qmax/1000/100,Qmax/1000/100],linestyle='--')\n",
    "axes[0].set_title('PCE(ours)')\n",
    "axes[0].set_xlabel('t/s')\n",
    "axes[0].set_ylabel('Q/100(kW/m^2)')\n",
    "axes[1].plot(DO_tk*np.sqrt(R0/g0),kQ*np.sqrt(g0*R0)**3.15*np.sqrt(Rho(DO_rk,Rhodelta=DO_Rhodelta))*DO_Vk**3.15/1000/100)\n",
    "axes[1].plot([0,np.max(DO_tk*np.sqrt(R0/g0))],[Qmax/1000/100,Qmax/1000/100],linestyle='--')\n",
    "axes[1].set_title('DO')\n",
    "axes[1].set_xlabel('t/s')\n",
    "axes[1].set_ylabel('Q/100(kW/m^2)')\n",
    "plt.suptitle(\"Monte carlo for heat rate\")\n",
    "\n",
    "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(12, 6))\n",
    "axes[0].plot(result_tk*np.sqrt(R0/g0),np.sqrt(L_(result_Vk,result_rk,CLdelta=result_CLdelta,Rhodelta=result_Rhodelta)**2+D_(result_Vk,result_rk,CDdelta=result_CDdelta,Rhodelta=result_Rhodelta)**2))\n",
    "axes[0].plot([0,np.max(result_tk*np.sqrt(R0/g0))],[nmax,nmax],linestyle='--')\n",
    "axes[0].set_title('PCE(ours)')\n",
    "axes[0].set_xlabel('t/s')\n",
    "axes[0].set_ylabel('n')\n",
    "axes[1].plot(DO_tk*np.sqrt(R0/g0),np.sqrt(L_(DO_Vk,DO_rk,CLdelta=DO_CLdelta,Rhodelta=DO_Rhodelta)**2+D_(DO_Vk,DO_rk,CDdelta=DO_CDdelta,Rhodelta=DO_Rhodelta)**2))\n",
    "axes[1].plot([0,np.max(DO_tk*np.sqrt(R0/g0))],[nmax,nmax],linestyle='--')\n",
    "axes[1].set_title('DO')\n",
    "axes[1].set_xlabel('t/s')\n",
    "axes[1].set_ylabel('n')\n",
    "plt.suptitle(\"Monte carlo for normal load factor\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
